{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "Union = pd.read_excel(\"Union.xlsx\", index_col=\"trade_date\")\n",
    "Intersection = pd.read_excel(\"Intersection.xlsx\", index_col=\"trade_date\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>000001.SZ</th>\n",
       "      <th>000002.SZ</th>\n",
       "      <th>000008.SZ</th>\n",
       "      <th>000009.SZ</th>\n",
       "      <th>000012.SZ</th>\n",
       "      <th>000024.SZ</th>\n",
       "      <th>000027.SZ</th>\n",
       "      <th>000039.SZ</th>\n",
       "      <th>000046.SZ</th>\n",
       "      <th>000060.SZ</th>\n",
       "      <th>...</th>\n",
       "      <th>601992.SH</th>\n",
       "      <th>601997.SH</th>\n",
       "      <th>601998.SH</th>\n",
       "      <th>603000.SH</th>\n",
       "      <th>603160.SH</th>\n",
       "      <th>603288.SH</th>\n",
       "      <th>603699.SH</th>\n",
       "      <th>603858.SH</th>\n",
       "      <th>603885.SH</th>\n",
       "      <th>603993.SH</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20140103</th>\n",
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       "    <tr>\n",
       "      <th>20140107</th>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>20140108</th>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140109</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>20140110</th>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140113</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140114</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140115</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140116</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140117</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140120</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140121</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140122</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140123</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140124</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140127</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140128</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140129</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140130</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140207</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140210</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140211</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140212</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140213</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140214</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140217</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140218</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140219</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20140220</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170821</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170822</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170823</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170824</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170825</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170828</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170829</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170830</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170831</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170901</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170904</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170905</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170906</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170907</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170908</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170911</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170912</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170913</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170914</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170915</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170918</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170919</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170920</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170921</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170922</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170925</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170926</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170927</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170928</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20170929</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>916 rows × 456 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            000001.SZ  000002.SZ  000008.SZ  000009.SZ  000012.SZ  000024.SZ  \\\n",
       "trade_date                                                                     \n",
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       "\n",
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       "trade_date                                                ...                  \n",
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       "\n",
       "            601997.SH  601998.SH  603000.SH  603160.SH  603288.SH  603699.SH  \\\n",
       "trade_date                                                                     \n",
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       "trade_date                                   \n",
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     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Union"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta\n",
    "import numpy as np\n",
    "\n",
    "def change_columns_index(signal):\n",
    "    new_names = {}\n",
    "    for c in signal.columns:\n",
    "        if c.endswith('SZ'):\n",
    "            new_names[c] = c.replace('SZ', 'XSHE')\n",
    "        elif c.endswith('SH'):\n",
    "            new_names[c] = c.replace('SH', 'XSHG')\n",
    "    signal = signal.rename_axis(new_names, axis=1)\n",
    "    signal.index = pd.Index(map(lambda x: datetime.strptime(str(x),\"%Y%m%d\") , signal.index))\n",
    "    signal.index = pd.Index(map(lambda x: x+timedelta(hours=15) , signal.index))\n",
    "    return signal\n",
    "\n",
    "def get_daily_weight(data,period):\n",
    "    data = data.fillna(0)\n",
    "    weight_list = []\n",
    "    for time_index, weight in data.iterrows():\n",
    "        weight_result = (weight/weight.sum())\n",
    "        weight_list.append(weight_result.to_dict())\n",
    "    stock_df = pd.DataFrame(weight_list, index=data.index)\n",
    "    if period>1:\n",
    "        stock_df = pd.concat([pd.DataFrame(0,columns=stock_df.columns,index=list(range(1,period))),stock_df],axis=0)\n",
    "    target = (pd.rolling_apply(stock_df, period, sum).dropna(how=\"all\")/period).replace(0,np.nan)\n",
    "    return target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/xinger/anaconda3/envs/IIA/lib/python3.6/site-packages/ipykernel/__main__.py:25: FutureWarning: pd.rolling_apply is deprecated for DataFrame and will be removed in a future version, replace with \n",
      "\tDataFrame.rolling(window=30,center=False).apply(func=<builtin_function_or_method>,args=<tuple>,kwargs=<dict>)\n"
     ]
    },
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       "                     000001.XSHE  000002.XSHE  000008.XSHE  000009.XSHE  \\\n",
       "2014-01-03 15:00:00     0.000412     0.000412          NaN          NaN   \n",
       "2014-01-06 15:00:00     0.000412     0.000823          NaN          NaN   \n",
       "2014-01-07 15:00:00     0.000412     0.001235          NaN          NaN   \n",
       "2014-01-08 15:00:00     0.000412     0.001622          NaN          NaN   \n",
       "2014-01-09 15:00:00     0.000412     0.002024          NaN          NaN   \n",
       "\n",
       "                     000012.XSHE  000024.XSHE  000027.XSHE  000039.XSHE  \\\n",
       "2014-01-03 15:00:00          NaN     0.000412          NaN          NaN   \n",
       "2014-01-06 15:00:00          NaN     0.000823          NaN          NaN   \n",
       "2014-01-07 15:00:00     0.000412     0.001235          NaN          NaN   \n",
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       "2014-01-09 15:00:00     0.000799     0.002024          NaN          NaN   \n",
       "\n",
       "                     000046.XSHE  000060.XSHE     ...       601992.XSHG  \\\n",
       "2014-01-03 15:00:00          NaN          NaN     ...          0.000412   \n",
       "2014-01-06 15:00:00          NaN          NaN     ...          0.000823   \n",
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       "2014-01-08 15:00:00          NaN          NaN     ...          0.001622   \n",
       "2014-01-09 15:00:00          NaN          NaN     ...          0.002024   \n",
       "\n",
       "                     601997.XSHG  601998.XSHG  603000.XSHG  603160.XSHG  \\\n",
       "2014-01-03 15:00:00          NaN     0.000412          NaN          NaN   \n",
       "2014-01-06 15:00:00          NaN     0.000412          NaN          NaN   \n",
       "2014-01-07 15:00:00          NaN     0.000412          NaN          NaN   \n",
       "2014-01-08 15:00:00          NaN     0.000412          NaN          NaN   \n",
       "2014-01-09 15:00:00          NaN     0.000412          NaN          NaN   \n",
       "\n",
       "                     603288.XSHG  603699.XSHG  603858.XSHG  603885.XSHG  \\\n",
       "2014-01-03 15:00:00          NaN          NaN          NaN          NaN   \n",
       "2014-01-06 15:00:00          NaN          NaN          NaN          NaN   \n",
       "2014-01-07 15:00:00          NaN          NaN          NaN          NaN   \n",
       "2014-01-08 15:00:00          NaN          NaN          NaN          NaN   \n",
       "2014-01-09 15:00:00          NaN          NaN          NaN          NaN   \n",
       "\n",
       "                     603993.XSHG  \n",
       "2014-01-03 15:00:00          NaN  \n",
       "2014-01-06 15:00:00          NaN  \n",
       "2014-01-07 15:00:00          NaN  \n",
       "2014-01-08 15:00:00          NaN  \n",
       "2014-01-09 15:00:00          NaN  \n",
       "\n",
       "[5 rows x 456 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Union_weight =  get_daily_weight(change_columns_index(Union),period=30)\n",
    "Intersection_weight =  get_daily_weight(change_columns_index(Intersection),period=30)\n",
    "Union_weight.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "并集组合（不对冲）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: better_exceptions will only inspect code from the command line\n",
      "         when using: `python -m better_exceptions'. Otherwise, only code\n",
      "         loaded from files will be inspected!\n"
     ]
    },
    {
     "data": {
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2JjIykmXLlvHxxx+/wF4QkPuxzXosY2Nj1frwpCpVquDh4aF3vhzzouPevXuc\nPn2anj17AtCzZ09Onz6drdWVn58fgwcPxsDAADs7Ozp27MjGjRsB+Prrrxk/fjwODg5ARh0yNTUF\nwN3dnapVq2JoaPgKS1V45HX/njlzhpYtWwJgZ2dH1apV2bBhgzp/zpw5tG3blgoVKuS4rZ9//pl3\n3333JZRC5Ie81gWNRkNcXBzp6ekkJSWRnJxMmTJlAGjRogXFihUDwNvbG0VRiIyMfLUFEa/c2LFj\n+eijj7C1tc3zMjnd24nCJ7+uEzlp27YtRkZGANSrV49bt26p9+hCiKJHzuZZvPfeezg7OzNp0iRW\nrlyZbX56ejoLFy6kffv2Oa5j0aJFVKpUiWrVqrFkyRJKliwJQGhoKC4uLmo6Z2dnbt68meu84sWL\nM3bsWOrWrcvWrVsZNWoUH3/8MTNnzsTY2Di/ii3Qf2xbt26Ng4MDfn5+fPfdd8+8TjnmRcfNmzcp\nU6YMWq0WAK1Wi6Ojo3q8MuV2TC9cuMD169dp2LAh1atXZ+bMmSiK8uoKUYjldf/WqFGD9evXoygK\nN27c4H//+58aWDxz5gy7d+9mzJgxOW7nzp077Nu3j759+768wogXkte68Pnnn3PlyhVKly6Ng4MD\nLVq0oH79+tnWt2rVKtzc3Chbtuwryb94OXr37o23tzfDhg0jOjo62/yAgABiYmLo2rWr3uU/+ugj\nvLy86NOnD2FhYTrznnZvJwqH/LhOAKxfvx5vb2+aN2/O0aNH9W5rwYIFtGnTRoJaosi5dC2cS9fC\nCzobhYJ8e7P46aefCA0NZfbs2Xz00UfZ5n/44YeYm5szYsSIHNcxdOhQLl26xLFjx5g1a9YLvx0a\nNmwYgYGB7Nq1i8uXL6PRaPD09GTgwIF06dJFZ9wN8fz0HdudO3cSHh5Oz549mTlz5ivLixzzoikt\nLY2zZ8+yd+9eDh06REBAAKtXry7obBUpX331FXfv3qVq1aqMHDmSpk2bYmhoSEpKCkOGDGHRokXq\nDa4+q1atomXLltjZ2b3CXIuXYePGjXh7e3P79m3CwsL4448/2LRpk06aQ4cO8fnnn/PLL78UUC5F\nfjh8+DBnzpzhxIkTKIqS7R4rOjqaCRMmZBt3KtPq1au5ePEigYGBVKpUiR49eujMf9q9nShacrpO\nQMY9+I0bNzh79iwfffQRHTp0yHYfvn79etatW8fChQsLIvtCPLeswQsJZEgQQ6++ffvy+++/65z4\nxo8fzz/SCpFmAAAgAElEQVT//IOfn1+eIrdeXl44Ojpy8OBBIOONbdZIcWhoqNqtJbd5mZKTk/ns\ns8+YO3cu33zzDb6+vvj5+TF9+nQePXr0IsV97eV2bA0MDBg0aNBzPYzKMS86nJycCAsLIy0tDcgI\nSISHh2c7Jk87pl27dsXExAQLCws6dOjA8ePHX10hCrG87l87OzvWrFnDmTNn2L59O3FxcXh4eHD7\n9m2uXbtG69atcXV15ZtvvmHp0qUMGTJEZ/nly5dLV5JCLq914fvvv6d3794YGBhQokQJOnTowO+/\n/67OP3r0KH369MHf35+KFSu+0jKI/JV57E1MTBg2bBhHjhzRmR8UFMTt27epXbs2rq6ubNq0iSlT\npjB9+nSd5bVaLaNGjeLYsWN6uwnou7cThceLXicAHBwc1C4jb7/9Nk5OTjqD+G/ZsoVJkyaxe/du\n7O3tX1HJhHhx+oIWr3sgQ4IYZIxfkbW52vbt27GxscHGxgaAiRMncurUKfz9/TExMclxPRcuXFD/\nv3HjBn///bd6Yu3WrRuLFy8G4J9//uHEiRNqn77c5mWaO3cugwYNomTJkjx8+BCNRoNGoyElJYXk\n5OR82AuvJ33H9v79+0RERKhpNm7ciJeX1zOvW4550ZE5mnnmG91ffvmFatWqZXuj361bN5YuXUp6\nejr379/H399fbd7cq1cv9uzZg6IopKSksH//fnx8fF55WQqjvO7fyMhI9RcoDhw4wLlz5+jVqxfO\nzs5EREQQHBxMcHAwo0ePZvDgwSxZskRd9n//+x8xMTG0atXq1RVMPLO81oVy5cqxa9cuICOgu2/f\nPqpUqQLAiRMn6NGjB5s2baJ69eqvtgAiXz18+JCYmBgAFEVh/fr1VK1aVSdNgwYNuHfvnvr979q1\nK9OmTWPy5MmkpqaqvwIFGfXJy8sLAwODp97bicLlRa8TgE5XosDAQIKDg9Ug544dOxg7diy7d+/G\n1dX1FZRIiPxxNeRujvNe60BGAQ4qWiA+/PBDpUyZMopWq1Xs7e0VDw8P5c6dO0qdOnWUKlWqKD4+\nPkrjxo2VU6dOKYqiKEFBQQqgVKhQQfHx8VF8fHyUjh07quvz8fFRwsLCFEVRlG7duikeHh6Kj4+P\nUr16dWX9+vVquvj4eKVr166Km5ubUqFCBcXf3z9P8xQl45cNWrVqpX6+evWqUqtWLaVy5crqCM3i\n2eV0bM+ePatUr15d8fLyUqpUqaK0a9dOuXbtmrpc1mO+bt06pUyZMkqxYsUUKysrpUyZMsr58+cV\nRZFjXtRcvHhRqV27tvLGG28otWvXVi5duqQoiqK0atVKOXHihKIoGb+OMXToUKV8+fJK+fLllcWL\nF6vLp6WlKWPGjFEqVaqkeHh4KGPGjFHS0tIURcn4VaQyZcooFhYWirm5uVKmTBll165dr76QBSgv\n+3fnzp2Ku7u7UrFiRaV+/frK33//rXdd+kagf++995RPPvnk5RZC5Iu81IWrV68qzZo1U6pUqaJU\nrlxZGTZsmJKSkqIoiqLUrFlTsbW1Vc/bPj4+ytmzZwusPOL5Xbt2Talatari5eWleHh4KF27dlXC\nw8MVRdG91mbVv39/9ddJ4uPjlRo1aqjX6xYtWqj1Kbd7O1E4veh1ol+/foqnp6fi7e2t1KxZU/nt\nt9/Ueba2toqjo6POeSMiIuLVFlCI53DxathT/15HGkWRkeeEEEIIIYQQQojCIq8tLYqZmuBcpuRL\nzk3h8nr+3p8QQgghhBBCCFEIPRnAqOTmmOP8hMSkV5KnwkSCGEIIIYQQQggh/rNyatXwhqsDWm3u\nw0SG3LqPS9mC++WzJwMYmdNe5zExZGBPIYQQQgghhBCvnX+C73DpWniuvwDiUtauUAYM9AU3XhcS\nxBBCCCGEEEII8VrLGqh4Mmjh7lowP8tb3rlUgWz3ZcspcJRX0p1ECCGEEEIIIcR/Xklrc+xsLHWm\n5fQwnbWlg6FW+1LzJZ6NtMQQQgghhBBCCPFayhqseN7WAZeuhfPwUd4G2CyMXVP0CQmLeK7lnrYf\n8qP80hJDCCGEEEIIIYTI4uGjJG6GRwL6x5948mE8M62+9E+mzfz8ssa1yLq93PKS13zqSxsSFsGj\nxGR1nr7gxIusPzfSEkMIIYQQQgghxGsp64N0GQfrZ17mRdIWlVYZ8HzleFnlk5YYQgghhBBCCCH+\n8yKj4omMis9xvkVxs2de57O0INDXdeXStfBC80sjeWlxkpdlcxtn5HlbX2QlLTGEEEIIIYQQQrzW\nsj5Q5/Zw/SwP4fnxwF4UPFk2J8eSL3V70hJDCCGEEEIIIcRrydLCDMdSeetG8iLyOvBnQcqv7h/F\nzUzyZT05kSCGEEIIIYQQQoj/vKw/sZr5wB4b9+iVBDGyDvz5PDLzW6qkJTZW5vmRJb3rLwqkO8lL\ndudBPM3HrSctLb1Atn/m6l16Td9aINsW2Ul9yB/jf9xPwLFrBZ0NVqxYQYMGDZ57+VatWrFy5Uq9\n6zI3N+f69esvnEfxagUHB6PRaEhNTS3orLzWPvvsMwYMGKB33owZMxg6dOirzZAokmbPns17772X\n43xXV1f27dv3Uradl2vAwYMHKVu27EvZvhCvg/LOpdT/X8UDfCU3xxz/stKXl/iHier/9yJjs82/\ndC08X8uQU94Ki9eqJUbfmduIikvCwECDoVaDh6stI7vUpJR18YLOWqGw5/h15m84gbGRFgMNONiY\nM6C1F3U9yuRp+fE/7qdpdVda1XV7yTnNH1If8ubM1bt8tPB3BrXxoUeTygWdnXzXsmVLateuzfTp\n03Wmb926lffff59bt25haPjip8qpU6dy9epV1qxZo04LCAjIMX18/ONBpwYMGEDZsmWZOXPmC+ej\nILi6uhIeHk54eDi2trbq9GrVqhEYGMiNGzdwdXV97vVrNBqKFSuGRqPBxMSEqlWrMmTIEHr06JEP\nuRf5xdz88VujhIQETExM0Gq1ACxevJjevXu/knx8/vnnL2W9qampGBkZqXUx0/Tp0xk7duxL2WZR\n5+rqyt27dzE0NESr1eLh4UG/fv0YMmQIBgYF/55t4sSJL2W9Bw8epEmTJmpdcXR0ZMKECQwcOFBN\nk/UaIIR4OYyNnu/+LuvglPk9KGdhaA3xssezyA8Ff4V4xaYPeottX3Rl/ZSOWJub8sOW0wWdpZfm\ned72V3YpybYvurJ5Zhfa1ndn9uqjxD9Kfgm5y64gWidIfXi6vSeDsShmzL6TN/I5R4VD//79WbNm\nDYqi6ExfvXo1vXv3zpcAhoBy5crxyy+/qJ/PnTtHQkJCvq3/zJkzxMfHc/nyZQYMGMCIESOYNm2a\n3rSKopCeXjCtoV5n8fHx6p+zszPbt29XP+sLYBTV1iznz5/XKWtOAQx95XvWMhfVfZTV9u3biYuL\nIyQkhAkTJjB37lwGDRpU0Nl66RwdHYmPjyc2Npavv/6awYMHc/ny5YLOVoFxdXXF2NiYiIgInenV\nqlVDo9EQHBz8QuvXaDQUL14cc3NzSpYsSdOmTfHz89NJ06hRI0xNTbGwsMDS0pIaNWowZ84ckpKy\nj2PQokUL9uzZw9SpU9FoNHz77bc687/99ls0Gg1Tp059oXxDxosMY2NjLCwssLCwoEqVKnz66afE\nxMSoaVasWIFWq8Xc3Bxzc3PKlSvHwIEDuXLlipoms6VgZhp7e3vatm3L3r17XziPRVleflHjaa6G\n3NH5nNNgnvpaSzxtm9dD7+U4Lz4hMcd5BgaPg+lZt5GXMmbt9vKqgirPup3XLoiRydhIy1s+ToTe\nfdwcJzk1jSXb/qb3jG10n7KFbzedICkl4wYhsxn+poOX6DZlC+9M9Wf38cfN/JJSUlm87W/6zNxG\nx0m/Mub7feqyAPtPh9B7xja6fr6ZdfvOq9NX7T7HjJVHmLP2KB0mbmLI/wVw634sv+y/QLcpW+g1\nfSsnL99W0+8+fp1Bc3fSYeIm+s3azo6jV9V5mXn0O3CRHlP9+dLvr2zl3nL4Cu/N28n96NwfHgwM\nNDSr4Upiciph9+PU6RdDIhj93V46TfqVoV/u4szVuwAs33mWoOsRLNhyivafbmLB5lN6u05k7Qaw\n5/h1Rn+/j4VbT9Pl882s2hPEnuPXGfP9PpZs+5vOn/1K31nbOX7xcaXec/w6/WZtp8PETfSdtZ39\np4JzLUdeSX3QXx8eJaVy+OxNRnSuQVhEPFduPlDnZR7fPSdu5FiWmauOMG/dMTpM3MTgeTt1lm8+\nbj1hEY/r1v/9cozlAWcBiEtI5vOf/qDb5C10/uxXPv/pj6fW2efVsWNHIiMjOXz4sDotKiqKHTt2\n0K9fP2JiYujXrx92dna4uLgwc+bMHB+AR40ahZOTk3rzk7nOXbt2MXv2bPz8/DA3N8fHxwfIuGH6\n6aef9K5Lo9Fw9epVlixZwtq1a5k3bx7m5ua0a9eO//u//6NLly466UeOHMmoUaPyY5e8FH379mXV\nqlXq55UrV9KvXz/182+//Ua1atWwtLTEyclJ58bPz8+PcuXKERub8f0MCAjAwcGB+/fvZ9uOra0t\nffv2ZeHChXzxxRdERmZciBs1asSkSZOoX78+xYoV4/r16yxfvpzKlStjYWFB+fLlWbx4sboeX19f\nfv31VwCOHDmCRqPht99+A2D//v1UrVoVgLS0NMaPH4+trS3ly5dX02QKDw+nffv22NjY4O7uztKl\nSwFITEzEzMxMvWGfNWsWhoaGahk///xzRo8eDWTcwA4fPpw2bdpgYWFBnTp1uHat4LtT5bfPPvuM\nHj160LNnTywsLFizZg1Hjx6lbt26WFlZUbp0aUaOHElKSoq6zLlz52jWrBk2NjY4ODgwb968bOtN\nTk6me/fudO/enZSUFJ2uJlevXkWj0bBq1SrKli2LnZ0dc+bMUZdNSEigT58+WFlZ4eHhwZw5c567\n1ZC+8umblpiYyMiRIyldujRlypRh7NixJCdnvEzYt28frq6uzJ49GwcHBwYPHvxceSmMSpQoQfv2\n7fHz82PlypUEBQUB5HoOdnFx4dSpUwCsXbsWjUbD+fMZ16Fly5bRsWNHIKMlXPfu3enXrx8WFhZ4\nenpy8uRJddtz586lTJkyWFhYULFiRfbv368u16dPHzXd6tWrcXFxoWTJksyaNUsn/+np6cyZMwc3\nNzdKlixJ9+7defDgAU+j0Who3bo1NjY2nD17Vmf61asZ1/SdO3fi4eGBhYUFZcqU4csvv9S7ru++\n+w4PDw9u3br11O0WRoUh2L1gwQLi4uK4ffs2X331FevXr6d169Y6LzoePnzIyZMn8fX1BaBChQo6\n1zfIuMZVqFAh3/L+8ccfExcXx/3791m+fDnHjh2jfv36PHz4UE1Tr1494uPjiYmJYd++fZiZmVGj\nRg31u5QpOjqa+Ph4zpw5w9tvv02nTp1YsWJFvuX1dZE1OJGamq4GKPQ9jOvrLpIf3T9u3c75HFOh\nXGm928yr/O6ektXTAjt58doGMRKTUzkYGEpll8fNZZb9doZb9+NYOK4FKz5tS0TMI9bsefxQ9iAu\nkYeJKfwyuQNje9RmweZTxCVk3Fgs2RbIP7ce8M2Hzfh1Rifea1tVpznp+Rv3+XlCa+Z+0Ji1e84T\nevdx9PTYhTCa1XBl84zOuJex5tMlh1AUhV8md6BP8yp8u+nxhdbK3JQZg97Cf1YXxr9Th8Vb/+af\nWw908hiXkMTqz9oxulstnTKv2RPE3hM3+HJYE+ysiuW6f9LS09lz/AaGWgO1e0VETAKf/fQHvd72\n5NcZnRncrirTVx4hOj6Rga29qVLelhGdarDti66M6FwjT8fhUmgkpW3M2TC1I72aeajTypayZOP0\nTnRvXIn5G46jKAqPklL50f80swb7snV2V775sBluZfJnEB6pD/rrw5FzNzEzNqShjxM1Kjqw90T2\n1hi5leXo+TAaVXNm88zO1PUsw4LNp556LCDjTXnz2uVY/Vk71nzWHmMjbZ6XfVZmZmZ0795d5wZk\nw4YNVKpUCR8fHz788ENiYmK4fv06hw4dYtWqVSxfvlzvumrVqkVgYCAPHjygV69edOvWjcTERFq2\nbMnEiRPp0aOHeuOQV0OGDKF37958/PHHxMfHs337dvr06cOuXbuIjo4GMt7Grl+/XicoUNjUrVuX\n2NhYLl68SFpaGuvXr9d5OChevDirVq0iOjqa3377jYULF+Lv7w9Ajx49ePPNNxk5ciSRkZEMGjSI\nn376CTs7uxy316FDB1JTUzl+/Lg6bfXq1SxZsoS4uDhcXFwoVaoUO3bsIDY2luXLlzNmzBhOn85o\njeXr68vBgwcBOHToEOXLl+ePP/5QP2fevC5dupQdO3bw999/c/LkSTZt2qSTj3feeYeyZcsSHh7O\npk2bmDhxIgcOHMDU1JRatWpx6NAhdZ0uLi4cOXIk2zYA1q9fz5QpU4iKisLd3Z1JkyY913Eo7LZs\n2UKvXr2IiYmhR48eGBoa8u233xIREcGRI0fYtWuXGmyKiYmhWbNmtGvXjtu3b3PlyhUaNWqks76E\nhATat2+PhYUF69evx8jISO92//e//3H16lV2797NlClT+OeffwCYPHky4eHhBAcHs3v3bp3uYPlR\nPn3Tpk+fzsmTJzl79ix///03R44c4YsvvlDXcevWLeLj4wkNDeXHH398ofwURrVr16Zs2bJqEDi3\nc3Bev6cA27Zt45133iE6Opr27dszYsQIAC5fvsyCBQs4ceIEcXFx7N69W2+g6sKFC3zwwQesXr2a\n8PBwIiMjdYIF33//Pf7+/hw6dIjw8HCsra0ZPnz4U8ubnp7Otm3biIiIwN3dXW+aQYMGsXjxYuLi\n4ggKCqJJkybZ0kyfPp0VK1Zw6NChIjtORkEHu7MqXrw4jRo1Ytu2bRw9elQnQL1//37q16+PiUnG\nry/UqlWLhIQENYB2/vx5EhMTqVXr8X1XVFQUbdu2xc7ODmtra9q2bavWnwcPHlC2bFm2b98OZLRa\nc3d3zxYYAdRrx7Zt24iMjNR7P6LVanFzc+PHH3/E19c3x9YgDg4OjBo1iqlTp/LJJ5+81i0Un7c1\nRk7dSLK2gnhaWkPDpz+O68tTXvKpb5u5dX3JKX1h7F7y2gUxpi7/k06TfqXTpF85feUO3RpXAjIe\nmnYeu8bQDtWwLGZCMVMjejb14GBgqLqsoYEBfd72xFBrQO3KjpiaGHLrfizp6Qq7j9/gg47VsS1R\nDK2BAZ7lbDE21KrL9mleBRMjQ9wcrSnvaMW18Gh1XpVydtSsVBqt1oC3fJyIiU+iR5PKGGoNaFTV\nmbsPHqpdOup4OOJoa4FGo8HbrRTVKzgQdP3xCdpAo6FfCy+MDbWY/NvPS1Fg0da/OXX5Dv/3QWOs\nzE1z3D8XQyPpNOlX2n6ykSXbA/mkV12sLTLS7z8VQu3Kpald2REDAw01KjpQoawNxy/eznF9T1PS\n0oyOb1VAqzVQ82tvXZzWdd3QGhjwds1yPIhNJCouo7mURqMh+E4MSSmplLQ0w9WhxHNvG6Q+PK0+\n7D0ZjG9VZ7QGBjSp5sLBwFBSn+iW8rSy1K7siNbAgGY1XLmeZV5uLIub8Ja3E6bGhhQzNaJXMw/O\nXc+5Od2L6t+/P5s2bSIxMaOerVq1iv79+6sP21988QUWFha4uroybtw4Vq9erXc9ffr0oWTJkhga\nGjJu3DiSkpJeSvPg0qVL07BhQzZu3AhktPSwtbWlRo28BQ8LSuYN6t69e6lcuTJlyjweb6dRo0Z4\neXlhYGCAt7c3PXv2VB/wAX744QcOHDhAo0aNaNeuHW3bts11W0ZGRtja2uq8CR0wYACenp4YGhpi\nZGREmzZtcHNzQ6PR4OvrS/PmzdUHJ19fX3X7f/zxB59++qlOwCHz4WjDhg2MHj0aJycnbGxs+PTT\nT9Xt3bx5kyNHjjB37lxMTU2pWrUq7733nnpjmrmN1NRUzp49y8iRIzl06BCJiYmcOHGChg0bquvq\n1KkTtWvXxtDQkN69exMYGPhcx6Cwa9CgAe3atcPAwAAzMzNq1apFnTp1MDQ0pHz58gwZMkQ9Dtu2\nbcPZ2ZlRo0ZhYmKCpaUltWvXVtcVExNDixYtqFy5Mj/99FOuYyxMnToVU1NTqlevjqenpxpo3LBh\nA5MmTcLKygonJyf1wTc33t7eWFlZqX+Zb/X1lU/ftLVr1zJ16lTs7OwoVaoUkydP1jnnGBoaMnXq\nVIyNjdV1/Nc4Ojry4MGDp56Ds35PDx8+nOP3FDL2c+vWrdFqtfTt21c9xlqtlqSkJC5cuEBKSgqu\nrq64uWUf22vTpk20bduWhg0bYmJiwowZM3Tq1KJFi5g1axZly5bFxMSEqVOnsmnTphy7/ISHh2Nl\nZYWZmRmdOnVi/vz5VKtWTW9aIyMjLly4QGxsLNbW1lSvXl2dpygKY8eOZc+ePfz++++5BncLu8IQ\n7H6Ss7MzNWvW1GmtuXPnTtq0aaOTLmsAZuXKlfTt21dnfnp6OgMHDiQkJITQ0FDMzMzU84mNjQ0/\n//wzgwcP5t69e4wZM4aqVavm+mLCwsKCt99+Wydf+nTu3DlPae7du/ef786UOUhl5i+T5DQ/64N8\ncTOTpw5uqW+QzidbQeSW1t3F4alpKrk5Yl7cFAONBgONhgrlHPI0QKi+9eVU1tzS57QfXMrY5rp/\n8jLveQcQfe06e08d2IDqFRxIS0/naFAY4384wNKPW6HRaEhKTmP413vUtAqQnv64+ZhlcWO02scX\nLFMjLY+SUol5mERyahqOJXP+qRsbi8cPiibGWhKTHl/UrLPOM9JSorgx2n8vjCZGGQ++j5JSMTcz\n5vjFcNbsOU/Y/TjSFYWklDTKlX78IF+iuAnGRo8flgHiE5PZeewak/q+SXEz41z3T2Xnknz9YTMe\nJaUw3+84Qdfv41vVGYC7UQ/548xNjp1/HPlLTU/Hx71UTqt7Kn0tALLuD1PjjCr6KDkVG0szJvV9\nk40HLzHf7zie5WwZ0q4azvb6T0Z5IfUh5/pwL+ohZ67e493W3gDUq1KGbzad4K8L4dT3evyWJ89l\nMdaSnJpGWlq6zn7TJzE5lUVb/+bk5dvE/9u6JSEplbT0dHVf5KcGDRpga2uLv78/tWrV4vjx42ze\nvJmIiAhSUlJwcXFR07q4uBAWFqZ3PV9++SXLli0jPDwcjUZDbGxstv69+aV///4sXLiQwYMHs2bN\nmmw3TIVR3759adiwITdu3Mh2c/bXX38xYcIEgoKCSE5OJikpiW7duqnzrays6NatG/Pnz1e7eeQm\nJSWF+/fvY2Njo05zcnLSSRMQEMC0adO4cuUK6enpJCQk4OXlBWQ0y71y5Qp3794lMDCQbdu2MWXK\nFCIiIjh+/LgaYAgPD9dZb9a6Eh4ejo2NDRYWFjrzM5ux+/r6MnbsWE6fPo2Xlxdvv/02gwYN4tix\nY7i7u1Oy5OM3Hw4Oj29yihUr9p8d9O/JY3Tp0iXGjRvHqVOnSEhIIDU1lTp16gAZQSJ9D5uZjhw5\nQmpqKhs3btRpCadPTvv39u3bOnl6Mn/6nD17NscuJ/qWf3JaeHh4rucce3t7jI1zv5YXdWFhYdjY\n2Dz1HOzr68v48eO5ffs2aWlpdO/enWnTphEcHExMTIza7QuyH+PExERSU1Nxd3fnm2++YerUqZw/\nf54WLVowf/58HB11b6if/K4XL15c5zsaEhJCp06ddAIbWq2Wu3fv6gRsMzk6OnLr1i2SkpKYMGEC\nBw4cULuQPenXX39l5syZTJgwAW9vb+bMmUO9evWAjK4BS5Yswc/PjxIlXuzFTmGQGQzw9fXVG+zO\nlDXYndlt6IcffsDb2/uFgt36ZAbVMu3cuTNba7g+ffrQoEEDZs6cyfr16zly5IhOULtkyZI63UAn\nTZpE48aN1c/NmzenW7duNG3alAcPHuh0LcotX5ndqfKa95zSAHnq/iQKVoXy+oMjr6PXriVGJq2B\nAQ28nTAw0BB0I4ISxU0wMdKy9ONWbJnVhS2zuuA/qwvbvuj61HWVKG6CsaGW8MiXe1OZnJrGjJVH\n6NqoEn7TOrJlVhdqVSpN1uEI9d2nWZgZM2PQW3zp9xfnb2RvVqePmYkRH3atyb5TwVy9FQVkBBya\n1XBV98+WWV3Y/kU33mma0Q1Eg+7GMwMQiSlp6rQHsboD0OR+W5ldzUqlmTu0MeundsCplCXfbMw5\nev4spD5kt/9UMOmKwuSfD9Njqj/9Z+8gOSWNvfk0wKeJsZak5Md1I7O1DcCmQ5e4dT+W70a+jf/s\nrnw1vGnGDOXJteSffv36sWrVKtasWUOLFi2wt7fH1tYWIyMjQkJC1HShoaF6b0gPHz7MvHnz2LBh\nA1FRUURHR1OiRAm1H+3THqJyo2/Zjh07cvbsWYKCgtixY8cr+2WHF+Hi4kK5cuXYuXMnnTt31pnX\nq1cv2rdvz82bN4mJiWHo0KE6fZADAwP5+eef6dmzJyNHjnzqtrZu3YqhoaHOm/ms+zEpKYkuXbow\nfvx47t69S3R0tE6/52LFilGjRg2+/fZbqlSpgrGxMW+++Sbz58/Hzc1N/ZWV0qVLc/PmTXW9oaGP\nW2tl3jzGxcXpzM+sP2+++SaXL19my5Yt+Pr64uHhQWhoKDt37tR5g/w6ebKuv//++1SpUoWrV68S\nGxvL9OnT1WPk5OSU69ggrVu3Zvz48TRt2lRvk/K8cHBw0OkykPVYPw993+Unpzk6OuZ6znmRc0lR\ncOLECcLCwtTgcm7nYHd3d4oVK8b3339Pw4YNsbS0xMHBgSVLltCgQYM8/8JJr169+PPPPwkJCUGj\n0fDJJ59kS/Pkdz0hIUGnG4KTkxMBAQFER0erf4mJiXqvF1mZmJgwd+5czp07p7YqeFKtWrXYunUr\n9+7do2PHjnTv3l2dZ21tzY4dOxg4cKDaHa0o69u3L+vWrWPFihV6g92NGzfGzs6OEiVKsGjRIp0X\nBZ8w+z4AACAASURBVJnB7qCgIMaNG/fUbekLduuTGVSDjHE6SpQokS346OzsjLu7OxMnTuSNN97I\nNj8hIYH3338fFxcXLC0tadiwIdHR0aSlPb4PGjJkCEFBQQwYMEAnQJaXfL1oGuCp6UTByTqGRtZf\nRXmdvbZBDEVR+F/QLeIeJeNsb4mBgYZWdd1YtPVv9WEqIiaBk5ee3lXCwEBDi9rlWLz1byJjHpGW\nns6F4AiSU9OeuuyzSE1NJyU1HStzE7QGGo5fDOf0lTtPXxDwcbdnQq96TFvxJ5dCs/f908eymAmt\n6pRnzd6MAYGaVnfh2IVwTl66TVp6OskpaZy5elcdcNHKwpTbDx4/uFuZm2Jbwoz9p4JJS09n11/X\nuf0CD/ZRcYn8L+gWj5JSMdJqMTM2zLebOakP2e09GUyf5p4sHNtC/ZvcvwEnLt4m9mH2kbqflZuj\nNb+fDiEtPZ0Tl25z9trjh4xHiakYGxlibmZMbEISq/cE5bKm/NGvXz/27dvH0qVL6d+/P5DxFq17\n9+5MmjRJHT1//vz5Os1bM8XFxWFoaIidnR2pqalMnz5d7ZsLGW9Pg4ODn6vPqb29PdevX9eZZmpq\nSteuXenVqxe1a9fG2dn5mddbEJYtW8aBAwcoXlz3p4zj4uKwsbHB1NSU48ePs27dOnVeYmIiffr0\nYfbs2SxfvpywsLAcxwJ48OABa9euZfjw4XzyySc53ghmtvaws7PD0NCQgIAA9uzZo5PG19eXBQsW\nqAGFRo0a6XwG6N69O9999x23bt0iKipKZ1BIJycn3nzzTT799FMSExM5e/Ysy5YtU+tPZqDkhx9+\nUNf55ptvsmjRotc2iPGkuLg4SpQoQfHixbl48aLO4Kvt27cnNDSUBQsWkJSURGxsbLZm4RMnTqRr\n1640a9ZMb7/3p+nevTuzZ88mOjqaW7du8cMPP7xwmZ6mZ8+eTJ8+nYiICO7fv8+MGTP0nnP+a2Jj\nY9mxYwfvvPMOffr0wcvLK0/n4Lx8T3Nz+fJlDhw4QFJSEqamppiZmekNfnTt2pUdO3bw559/kpyc\nzOTJk3XO50OHDmXSpElqwOX+/fts3bo1T3kwNjZm3Lhx2X7qGzLOVWvXriUmJgYjIyMsLS2z5a9R\no0asXbuWzp0759o1oigo6GD3k27evMmpU6d46623gIxWGK1bt9abtl+/fnz11Vd6u4F89dVXXL58\nmb/++ovY2Fh17JbM/KelpTFkyBD69evHjz/+qA7qmpP4+Hj27dun5isnW7ZsyVOaUqVKUbFixVzT\niYKTU5eQ19lrF8SYvOww7T/dRMdJv7I84Nz/s3ffcVFcWxzAf0tVWYpYQKyIooKCIEoXBMSCLba8\noFGjifpiQxM1mmLsJbaoL4nR2LvRWGNBBewFEzUKCgqigmBBOgK7e94fuBOWXYpK2+V8Px8/H7wz\nc++de2dgOcyci6n/cRbyKnwaYA+LumJMWhWMfjN/x/RfQvG4wMocxRndpz0sG5hg/MqTGPDtH1h/\n9KbSko3vq1YNXXzezxHztlxA/2/2I+TvOLjYFh/hL6hDK3N88aEzvvvtrELyx+J80LkVrkU+RUxC\nCurXNsD3n3hi5+kIDP7uAIbMPYS9oXeF8/zA0xrnbj5B/2/24X9/5D/eFjSoI/aG3sXAb/9AXFIq\nbJrVffsTf0NGhH1h9/DRnIMY8O1+3Ip5hokDnN65PoCvh6Kuh8i4F0h6lYk+7i1halRT+OfatiEs\n6ooR8ndcEbWW3uf9HHE5Ih79v9mPM389hFvbf/vev3Mr5OZJMPC7PzDpx1Nwal3+j881a9YMbm5u\nyMzMRJ8+fYTy1atXw8DAAM2bN4eHhwcCAwMxcuRIpeO7deuG7t27w9raGk2bNkWNGjUU/hIjfzWi\nTp06Cu8zl8aoUaMQEREBExMT4bFZIP+Vkn/++UctXiWRs7KygpOT8n37008/4bvvvoOhoSHmzJmj\n8JfGGTNmoHHjxvjvf/8LfX19YVUHefJFALC3t4dYLEaLFi2wfv16rFixQuUvBHKGhoZYtWoVBg8e\njNq1a2PHjh0K8w7k/3KUnp4uvDpS+P8A8Nlnn6Fbt26wt7eHo6Oj0ofunTt34uHDh7CwsMAHH3yA\n2bNnw8/PT6GNvLw84UO0qjaqs2XLlmHz5s0wNDTEmDFjhGSYQP5qFsHBwdi3bx/MzMxgbW2tkEdF\nbvbs2ejRowe6du0qJMMtrdmzZ8PMzAzNmjWDv78/Bg8eLCTzK4qtra2whKFYLC7VX4QLmjVrFuzt\n7dG2bVvY2dnB2dlZ4bF0TdO7d28YGhqicePGmD9/PqZMmaKQrLCk78GluU+LI3+do27dujA3N8ez\nZ88UEqnK2dra4n//+x8CAwPRoEED1K5dWyGB5qRJk9CnTx/4+/vD0NAQLi4uuHJFeVWwoowcORKP\nHj0SkjsWtHXrVjRr1gxGRkb45ZdfsH37dqV9unbtig0bNqB3795CgmJ1VRWC3VlZWQgLC0Pfvn3R\nqVMnIXChKh+G3IcffoiTJ08q/Pwq2PeaNWvCxMQEycnJSquiLFiwACKRCBs2bMDUqVMxbNgwhac0\n5HJycnD9+nX069cPtWvXxieffKK0j1QqRWxsLCZMmIDQ0FDMmjVLZX+TkpKwZs0azJ49GwsXLiz1\nk0uMVQnEGGNMLcXFxVHNmjUpNTW1srvCWLWwatUq8vHxqexuMKZxmjZtSsHBwUrleXl5BIBiY2Np\n79691KRJExKLxRQQEEDjxo2jIUOGEBFRUFAQde/eXTjuxo0bVLt2bYqKiiIiIgBUq1YtMjAwoNq1\na5O3tzdt375doS0vLy/S19cnsVhMYrGY2rdvT/PmzaPs7GwiInr16hXVrVuX8vLyhGNmzZol9KGw\nIUOG0KxZs4iIKD4+nry8vMjAwIBatmxJv/zyCwGgvLw8Cg8PJxMTE4qOjiYiIolEQm5ubjRv3jwi\nIho+fDjp6uqSWCwmAwMDsrGxoWnTptGrV6+EtjZu3EhaWlpkYGBAtWrVoiZNmtCwYcMoIiJC2Cc2\nNpYACPvUq1ePevToQceOHSvdJDFWhYiIyvjPw4wxxsqdTCbDlClTkJaWhg0bNlR2dxjTSPHx8YiL\ni4OLiwvu3buHgIAATJkypVSrlDDGNMuePXvw+++/Y8+ePZXdFcaqPX5uiDHG1ExmZiaMjIwQHBys\n9EgqY6zs5OTk4LPPPhOWMxwwYADGjBlT2d1iTKOEhoZCR0cHz57lL6V+7do1iEQiPHz4sNR1jBgx\nAi4uLvDz80P//v2FnBLff/897O3t4evrix49ehS7msfhw4fh4uICV1dXLFu2TCifPHkyPD09sXPn\nTkyePBkJCQlwdHREjRo1hCV0Hz58CDMzM3h7e8Pf319l/fJ6Jk2aJJRt2bIFvr6+8Pb2Vlr57O+/\n/0a7du0UVjsqqo9yt2/fhoeHB9zd3YUVTlSVFfTDDz/Aw8MDQ4YMQV5eXpFlcunp6ejduzfc3d2F\nZWVVlRVnzJgxcHd3h4eHh9CnhIQE+Pj4wM3NDadOnQIAbNiwAZaWlgp5cF6/fo1Ro0bBx8cHEyZM\nKNUYzJ8/HxYWFvjmm29U9qd3797w9PSEr6+vkMx579696NSpE5ydnVXmt1E1n6rK5FSdn6qygrZv\n3w43Nzf06tVLyLOmqqyw2NhYeHp6onPnzggMDBReTercuTO8vLzg6+sr3G+lqQ/Iv8fe5p4sd5X9\nKAhjjDHGGGOsegoJCaEOHTrQr7/+SkREM2bMICcnJ4qNjS11HcOHDxdex7h9+zZ5enqSTCajWbNm\nCa+pPH78mJydnSkzM1NlHXFxcSSRSEgmk1Hnzp0pJSWFrl+/Tp9++ikREY0dO5auXr1K2dnZlJyc\nTF5eXsKrJbGxsUW+VkJEKut58uQJjRw5sshj0tLSKCMjg9zd3YvtY0H9+vWjR48e0ZMnT6hPnz5F\nlsklJSVRjx49iIho0aJFtGfPHpVlBS1btoy2bdtGEomEPD09KScnR2VZcWJiYoiIKCoqivr3709E\nRBMmTKDz589Teno6eXl5ERHR8+fPKTo6WmFsFy9eTKdOnSqyblXnm5iYSGfOnKGvv/662P6cPHmS\npkyZQkRErq6ulJmZSVlZWdS5c2eF/VXNp6qyglSdn6oyudzcXPLw8KC8vDzatWsXLVmyRGWZKsnJ\nycK1MXPmTDp06JBQJxHRpk2b3qo+ovx77G3uyfLGT2IwxhhjjDHGKo2Pjw9Onz4NALhz5w5sbW0B\n5K844uXlBWdnZyxYsAAAsGbNGqxZswZZWVnw9vZWWMYayE/CamlpqbDkNQA0atQI3bp1w7Vr11T2\noUmTJtDW1oZIJIKOjg60tLRw+fJldO3aFQDg5+eHS5cuoUaNGqhdu7bS8SEhIfD09MSKFSuUtqmq\n58SJE5BKpfD19cWECROUEnkaGhoqJTdV1ceCXr16hcaNG6Nhw4ZCImNVZYsWLUJ8fDzCw8Ph7e2t\n0C9VZQCEpx7k56KtrQ17e3vcvXtXZVlxLC0tAQC6urrQ1tYGkL98rZubG8RiMQwNDZGWloa6detC\nR0dH4djQ0FAcOnQI3t7eOHTokFLdqs7XzMys2BUNVfXHysoKmZmZyMjIgJGRkcL+quZTVVliYiLm\nz59f5PmpKtu0aROuX7+O6OhotGvXDjo6OkJ9qspUqV27NoyNjZXOSVdXFwCQnZ0NW1vbEuuLjY2F\ns7Mz+vTpI6ySp+qe7Nu3L169egUACAoKwvXr1zFz5kx4eHigS5cuSEgo++VgOYjBGGOMMcYYqzR6\nenqoUaMGLl++jDZt2gjlrVq1QmhoKK5cuYLg4GBkZ2dj3LhxOHr0KD777DNMnToVhoaGSvVZWFgg\nMVF52fmiygs6duwYrKysYGhoiJSUFOEXWGNj4yJXOGrQoAGioqIQEhKCU6dOKb22oaqepKQk5Obm\n4vTp06hVq1apl+Qt3MeCCi77S2/SHqoq++qrr4Rf8gv3q6hzXr16dZHnoqrsyZMnGDRoEHx8fLBr\n1y5cvHgRP//8s0J/Z8yYISyHK5VKhUBDcWP94MEDBAQE4OjRo5g7d67wSk9xY1AaUqkU8+bNE14Z\n/OCDD+Dg4ID27dsrvbZS2jEwNzfH119/XeT5qSobMWIEOnTo8FZzU5SEhAQEBwcLrzg9evQIrq6u\nWLNmDdq1a1difT/88AOWL1+O/fv3C8uUq7onBw0ahH379kEmk+HmzZvo0KEDLly4gLNnzyIkJAQN\nGpT9KoMcxGCMMcYYY4xVqp49e2Ls2LEKS1XHxsaiZ8+e8PLyQmRkJJ49ewaRSIShQ4ciPDy8yOVO\n4+PjVf7iVFS5XExMDJYsWSI8TWFsbCzkCUhLS4OJiYnK4/T19WFgYAAdHR306tULt2/fxtatW+Ht\n7Y1FixaprMfY2BheXl4A8p9EiYyMxA8//ABvb29s2rSp1H0sqODTBvKnNFSVyRXVr+LOubTH3Lp1\nC8uWLcO2bdtw5MgRfPPNNwr5QlauXAkbGxt4eHgo9a24sZaPm4GBAVq0aIGkpCQhr0hiYmKx5yv3\n/PlzeHt7C0+cAMAXX3yBYcOGwcrKCgAwZ84cREREIDIyUmnJ9ncZN1XnV9w5v0sbBeXk5GD48OFY\nt26d8DRLkyZNcOnSJcyePRtLly4tsb6YmBg4ODhAR0cHdnZ2AFTfk/369cPhw4dx7tw5YXnradOm\nYfjw4QgKCkJWVlaR/XxXHMRgjDHGGGOMVaqePXuiQ4cO6Nixo1D2888/Y/r06QgLC0OLFi1ARMjM\nzMT69esxePBgbN68WameyMhIxMXFoXHjxgrl8fHxCA4OVqi/oPT0dIwYMQK//fab8BqHq6ur8JrL\nqVOn4OLiUuSxchcuXICVlRU+/vhjhIaG4quvvlJZj5ubm/DExo0bN2BpaYmpU6ciNDQUI0aMKHUf\nCzI1NcWTJ0+QkJAg/IVdVZlcx44dERYWptAvVWUFyc9FKpXixo0baN26tcqynj17okmTJrCwsMC2\nbdtw5swZIUBw8uRJXLx4USHRpp2dHS5duoTMzEykpaUp9VVOPm5SqRQPHz5EvXr1cPr0aYSGhsLc\n3LzY85WrV68eQkNDERoaCgD47bffIBKJMGzYMGEffX191KpVCwYGBsjNzVU5BgXHqKRrRdX5FXfO\n1tbWuH37NqRSqVCfqjIASklhAWD06NEYN24cbGxsAAB5eXnCkylGRkaoWbNmkfXJWVpa4ubNm5BK\npfjnn38AqL4nxWIxjIyM8OOPP+Kjjz4CkB+Y27p1K+rXr48jR46onIf3UpkJORhjjDHGGGPVV0hI\niFLCRXkSwWPHjpGtrS0NGjSIunTpQrGxsTRp0iQ6fvw45eXlka+vLyUmJtLw4cOpU6dO5OvrS/36\n9ROSfM6aNYvs7OzIx8eHunfvTuHh4UX2Y8GCBdSoUSPy8vIiLy8vIdnjxIkTycPDg8aPH09E+ckR\nfX19ycTEhHx8fOjy5ct09OhRcnR0JFdXV5o2bZrK+gvXQ0T0xRdfkJeXFw0YMEApGeajR4/I19eX\njI2NydfXl2JjY4vso9zNmzfJzc2N3Nzc6O+//y6ybOHChfTkyRMiyk/e6e7uTh999JHQB1Vl8n6n\npqZSQEAAubq60saNG4ssK461tTU5OTmRl5cXjR49mojyE6926dKFXFxc6MSJE0REdPjwYXJ3dydz\nc3MhAWhCQgJ17dqVnJ2daf369Up1qzrf9evXk6OjIzVr1ow+//xzpWP09PTIw8ODvLy86LvvviMi\noo0bN1KnTp2oU6dOtG7dOqVjVM1n4bKnT5/SvHnzijw/VWUbN24UrtMtW7aQq6sr9ezZU0jUqaqs\ncFLQixcvklgsFq6T/fv3U1xcHHXu3Jm8vb2pW7du9PTp0yLrk7t//z516tSJevfuTT4+PkXek0RE\nR44cofbt2wvHdu3alTw8PMjDw0NoqyyJiN7iZSHGGGOMMcYYY4xVuhcvXmD16tWYPXt2pfbjzz//\nxJ07dzB16tQKaY+DGIwxxhhjjDHGGHtr+/btw4oVK3Dw4EHUqVOnQtqsdjkxjhw5ImSatbe3x/79\n+wEAR48ehaOjI9q1awcvLy/ExsaqPH7jxo2ws7ND+/bt0a5dO6xatUrYJpVKMW7cOFhZWaFFixZY\nv359qbZt2LABNjY2cHBwwF9//SWUjxw5EufOnSvrIWBvfPnll7C0tIRIJMLt27cBAA8fPkT79u2F\nf82aNYOpqanK4991vvlaqJqioqLg6uoKa2truLq6Ijo6WmmfuXPnwtbWFnZ2dujQoQNOnDghbJs/\nfz7s7OyE7y+7d+8Wtt27dw8+Pj6ws7ODnZ0dgoODK+ScqprZs2cr3G+XL1+Gvb09rK2t4e/vj2fP\nnqk8LioqCt7e3mjfvj3atGmD77//XtiWlZWFDz/8EC1atEDr1q0V3rssbpt8Ll1cXBAXFyeU9+zZ\nE/fv3y/jM2cFleZeK+775Pfff4/69esL36fHjRuncOzq1avRunVrtGvXDu3bty/382Hv532vh+I+\nlwHAnj170K5dO7Rt2xbt2rVDUlJSuZ8TY4xVJwMGDMD58+crLIABoHrlxJDJZGRiYkL//PMPEeW/\nMyUWi+nFixdUp04dunfvHhERbd26lbp166ayjtTUVJLJZERElJaWRk2aNKGbN28SEdHmzZvJ39+f\npFIpPXv2jBo2bCi8J1TctmbNmlFGRgaFhYXRgAEDiCj//cBPP/20vIaCEdG5c+fo0aNH1LRpU+Ga\nKGzSpEk0btw4ldvedb75WqiaunTpQlu3biWi/O8BXbp0Udrn+PHjlJmZSUREN27cIGNjY8rKyiIi\nUniPMD4+ngwNDSk5OZmIiFxdXWnLli1ERBQVFUUNGzYU6qkurl+/Tt27dxfuN6lUSlZWVnTu3Dki\nIpo7dy598sknKo/t27cvrV69moiI0tPTqUmTJnTlyhUiIpo9e7Zwf0RFRZGZmRmlp6cXuy01NZWs\nra1JIpHQ5s2b6YsvviAiok2bNtHcuXPLbxAYEZXuXivu++SsWbOEOSts37595OnpSWlpaURElJiY\nWD4nwcrM+14PxX0uu3btGrVp00Z4HzslJYWys7Mr4KzY2wgJCSFtbW1KSkoiIqKrV68SAGGOS2P4\n8OHk7OxMvr6+9MEHH5SYE2Pjxo1kbW1NPj4+5OPjQydPnlSqc/To0eTm5kbu7u7CNRUfH09dunQh\nV1dXCg4OJiKi3377jZo1a0ZDhgwRjpW36+XlRcuWLVOqW1U92dnZNHLkSOrSpYtCngW5efPmUYMG\nDRTyh6jqY0FLliwhd3d3CgwMpNzc3CLL5NLS0qhXr17k5uZGmzdvLrKsoNOnT5OLiwt5e3vT48eP\niywrSkxMDHl4eJCnpyd99NFHJJFIiIho27Zt5OrqSgEBAZSamkpERH369CFjY2NhzIiIpk6dSm5u\nbuTh4UFRUVEljkFubi65uLiQgYGBcJ0UdPnyZXJ1dSV3d3cKCgoqto8VPW5BQUHk4eFBEydOLLas\nsJSUFAoICCAvLy9asWIFERHFxsZS/fr1ycvLi7p27Srsa2RkJOTSePnyZZF1yvPWVJZqF8QwNTWl\n8+fPExFRWFgYtWzZkq5evUo2NjbCfi9fviQA9Pz582LrS0xMpAYNGtCtW7eIiKhnz560d+9eYfu4\nceNoyZIlJW6zsrKiFy9e0J9//ikk0PH09Cz2wmFlp6ggRk5ODtWtW5euX7+u8rh3nW++FqqepKQk\nMjY2Fn4oSSQSMjY2pmfPnhV5jEwmIyMjI5U/ZO7du0dGRkb04sULIiKqVauWQl3t2rWj33//vYzP\noup6/fo1ubi4UGxsrHC/Xb16lWxtbYV9nj9/TgYGBiqP79evn5AYKykpiZo2bSr84LSxsaFr164J\n+wYEBNCePXuK3ZaRkUFWVlaUnZ1NP/30E82YMYNevHhBnp6eSonVWNkq7b1W3PfJ4oIYbm5udPr0\n6XLqPStrZXE9FFT4c1lgYCD99ttv5XgGrCyEhIRQhw4d6NdffyUiohkzZpCTk9NbBzHkv5Devn2b\nPD09SSaT0axZs4RfeB8/fkzOzs6UmZlJGzduFJI1Jicnk4eHB8XHxyvUKU+aGRUVJSSVnDBhAp0/\nf57S09OFZIrPnz+n6OhopSBGwV+0C1NVz+LFi+nUqVNFHpOYmEhnzpxRCGKo6qNcUlIS9ejRg4jy\nE3Xu2bNHZVlBy5Yto23btpFEIhF+JqoqK8jb25vS0tLo8uXLQtJMVWVFSU5OFv4QNHPmTDp06BDl\n5uaSh4cH5eXl0a5du4T7PSEhQWFsX758KQQ+z58/LwQdihsDmUwmJINVFcR4+vSpEOwMDAykW7du\nqexjRY/b9evXhT/MjB07lq5evaqyTJUlS5bQjh07iIiof//+9Pz5c4qNjVW4ZuXc3d1V1lFYZQcx\nqtXrJCKRCHv27EHfvn3RtGlT9OvXD1u2bIG1tTUSExNx7do1AMD27dsBAI8ePVJZz6FDh2Bra4um\nTZti6tSpaNeunbB/06ZNhf2aNGmCx48fl7htyZIl6Nq1KxYtWoTvvvsOixYtwmeffVbkawysYhw6\ndAgNGzaEo6Ojyu3vOt98LVQ9jx8/RsOGDaGtrQ0A0NbWhoWFhTAvqmzZsgVWVlZo1KiRUPbLL7+g\ndevWcHBwwK+//io8VtehQwfs2LEDABAeHo579+4pvMKg6b777jsMHToUzZo1E8oK3wd169aFTCZD\ncnKy0vErV67E7t270bBhQzRr1gxTp04V6nqXe83AwABTpkyBi4sLDh48iEmTJmHatGmYN28e9PT0\nyvjsWUGlvdeKm1cA2LVrF+zs7ODv749Lly4J5REREbh8+TLc3Nzg5OSEdevWlfMZsfdRVtdDUZ/L\nIiIiEBMTg86dO8PR0RHz5s0TlhhkVYuPj4+wPOWdO3dga2sLIH/pUS8vLzg7O2PBggUAgDVr1mDN\nmjXIysqCt7e3wvKmAGBrawtLS0ulz/GNGjVCt27dhM/7crVr18bIkSOVXvW0tLQEAOjq6grX6D//\n/AM3NzeIxWIYGhoiLS0NdevWhY6OjtI5TZ8+HX5+frhx44bSNlX1hIaG4tChQ/D29sahQ4eUjjEz\nM4NIJCqxj3Lh4eHw9vYGAPj5+eHSpUsqywBgwoQJAPJf8+zatSu0tbVhb2+Pu3fvqiw7fvw4jh49\niqysLNSsWROGhoZwdnbGnTt3VJYVp3bt2jA2NlY4j+joaLRr1w46OjoK/WzQoIHCsWKxGMbGxpBK\npUhJSVF6nUHV+YpEIpiZmRXZH3Nzc9SoUUOhP6r6WFB5jltQUBCkUqlQX8FzUVWmSkxMDOzs7AAA\nNjY2wj0QEhICT09PrFixQtg3MjISnp6e+Oqrr5S+X8bGxsLZ2Rl9+vRBTEwMANX3aN++ffHq1Suh\n/9evX8fMmTPh4eGBLl26ICEhocjxL61qFcSQSCRYuHAhDh48iLi4OBw+fBiDBw+GtrY2du/ejcmT\nJ8PJyQnPnj2DiYmJym9IANCnTx/cuXMHUVFR2Lp1K+7du/de/erfvz/++usvhIWFQVtbG1euXMGg\nQYMwbtw4DBo0SOn9TlYxNmzYgJEjR1Zom3wtqIewsDB8++232Llzp0L52LFjhR9c8+fPx8uXLwEA\nmzZtwpkzZ9C+fXssX74cHh4eRX5/0TTyD02ff/75O9exdu1afPzxx4iPj8eDBw+watUqXLly5b36\n9fnnn+PGjRs4fvw47t27B5FIBFtbW3zyyScYMGCAQk4TVrWMHTsWsbGxuHXrFqZOnYq+ffsK95pU\nKsXjx49x/vx5/Pnnn1iyZAnOnj1byT1m5a2oz2VSqRS3bt1CcHAwwsLCcOzYMWzdurWSe8tU0dPT\nQ40aNXD58mW0adNGKG/VqhVCQ0Nx5coVBAcHIzs7G+PGjcPRo0fx2WefYerUqTA0NFSqz8LC7Rbb\n+gAAIABJREFUAomJie9dDgAzZszAxIkTAeRfU/JAgrGxMVJSUlQeM3HiRFy/fh0///yzECAoSFU9\nDx48QEBAAI4ePYq5c+dCIpGorLukPsqlpKTAyMhIoQ1VZUB+LqG3OaZ79+4ICAhQ2CY/L1VlQH7y\nRx8fHwwbNgxXrlzBb7/9ppD/LSEhAcHBwfD39y+yn4Xp6enB0tISrVq1wvjx4zFq1KgSx6C0bt26\nhefPn8PGxkZlH0tqp6zGbeXKldDW1n6r+SysVatWCAsLg1QqxdmzZ5GSkoIGDRogKioKISEhOHXq\nFG7dugUAiI6OxtmzZ/Hq1SscPnxYoZ4ffvgBy5cvx/79+4Wfu6ru0UGDBmHfvn2QyWS4efMmOnTo\ngAsXLuDs2bMICQlRCka9i2oVxLhx4wYSEhLg7u4OAHB3d4eBgQEiIyPh5+eH8+fPIzw8HOPHj0d2\ndjasrKyKra9Jkybo1KmTkCyuSZMmCn9dffToERo3blzitoKCgoKwYsUKbN++HfXq1cPevXvxxx9/\nCNEuVjHi4+MRFhaGIUOGFLnPu843XwtVT+PGjREfHy/8wJBKpUhISFA5L5cuXcLQoUNx4MABtGrV\nSmV97dq1g4WFBUJDQwEAzZs3x8GDB3Hjxg3s2LEDT58+VfihqMnCwsIQGRkJS0tLNGvWDE+ePEG3\nbt1w//59hfvgxYsX0NLSUvnU0apVqzB8+HAA+X+F8fHxEX4xfd97LTc3F9988w0WL16MlStXwsvL\nC7t378acOXOQnZ1ddgPBAJT+Xitu7szNzaGrqwsA6Nq1Kxo3biwki23SpAk++ugjaGlpoX79+uja\ntSuuXr1aEafG3kFZXA+F9yv8uWzgwIHQ19eHoaEh+vbty9dDFdazZ0+MHTsW/fv3F8piY2PRs2dP\neHl5ITIyEs+ePYNIJMLQoUMRHh6OgIAAlXXFx8er/EXpbctXrlwJGxsbeHh4AAC0tP791SktLQ0m\nJiYq25f/LGvZsqVQNmTIEHh7e+PGjRsq6zE2NoaXlxcMDAzQokULJCUlwdfXF97e3kUGWFT1Uc7Y\n2BhpaWlKbRQue59jCm4D8p+mUlUGAMnJyTh16hSGDBmCSZMm4c6dO0Ly5ZycHAwfPhzr1q2Djo5O\nif2Ui4yMRHR0NKKiorB37158/fXXCA4Ohre3N4KCgkpdz9atW+Ht7Y1FixYJfR0/fjx+++03YZ/C\nfayocXvXNgr67LPPcPHiRfTo0QMWFhYwMzODvr4+DAwMoKOjg169egk/R01NTSESidCvXz+hTC4m\nJgYODg7Q0dERnuxQdY/269cPhw8fxrlz59C5c2cAwLRp0zB8+HAEBQUhKytLZT/fRrUKYjRq1AhP\nnjwRIvSRkZFISkqClZWV8M1BJpNh5syZGDt2LAwMDJTqiIyMFL5+8eIFQkJChMcWBw0ahHXr1kEm\nk+H58+c4cOAABg4cWOI2ua1bt6JTp06wtrZGZmamEKEViUTIzMws+wFhRdq8eTMCAgKKzbL7rvPN\n10LVI1/pQP5kxc6dO+Hg4IB69eop7Hft2jV8+OGH+P3335VeM4qIiBC+jo2Nxd9//y0EKp49eyY8\nkrdp0ybo6+vD19e3PE+pyvjqq6+QkJCAhw8f4uHDh2jUqBFOnDiBqVOnIjs7G+fPnweQ/yrOoEGD\nVNZhaWmJ48ePAwDS09Nx7tw5tG3bFkD+/bR27VoA+X89uHbtGrp3717iNrnFixdj1KhRqFOnjnCv\niUQi5OXlITc3t+wHpJor7b1W3PfJ+Ph4Yb8bN27g4cOHQkAxMDBQuFYyMzNx7tw52NvbV8SpsXdQ\nFtdDcZ/LAgMDcfLkSRAR8vLycPr0ab4eqrCePXuiQ4cO6Nixo1D2888/Y/r06QgLC0OLFi1ARMjM\nzMT69esxePBgbN68WameyMhIxMXFKQW64uPjERwcrFA/kP9X9M2bNwuP5cudPHkSFy9exDfffCOU\n2dnZ4dKlS8jMzERaWprCX84Lkv9i+eLFC+GJiu3btyM0NBTt27dXWY+bmxtu3boFqVSKhw8fol69\nejh9+jRCQ0Nhbm6ush1VfZTr2LEjwsLCAACnTp2Ci4uLyrKCXF1dcfr0aUilUty4cQOtW7dWWSZn\nYGCA7OxsZGRk4OrVq7CxsVFZBuT/Iq2lpYVu3brh8uXLWL58uRDMGT16NMaNGyfsa21tjdu3b0Mq\nlarspxwRwcTEBFpaWqhbty5SU1PRtWtXhIaGYuXKlSWer9zHH3+M0NBQfPXVV5BIJBg6dCiWLl2q\nMO6F+1hR41a4jYLnoqpMIpEorcJkYGCAbdu24dixY5DJZHB1dVV4DevChQuwsrJCZmamEFSWlxVk\naWmJmzdvQiqV4p9//gGg+h4Vi8UwMjLCjz/+iI8++ghA/itjW7duRf369RVWi3tnlZaNo5Js27aN\n2rZtS3Z2dmRnZ0d//PEHERGNGjWKWrduTc2bN6exY8cqZK/u0aOHkBwuKCiIbGxsyN7enuzs7GjV\nqlXCfhKJhMaOHUvNmzen5s2b09q1a0u1jSg/MU3BpC8vX76kzp07k62tLY0ePbrcxqM6mzBhAjVs\n2JC0tbXJzMxMIblry5Yt6dixY0rHFLwW3nW++VqomiIjI6lTp07UsmVL6tSpE929e5eIFOfcycmJ\n6tatS/b29sI/eQK5QYMGCd8bHB0dadeuXULd69atoxYtWlDLli2pe/fulZoIqbIVTKR74cIFatu2\nLbVo0YL8/PwUVpKwt7cXkqyFh4eTq6sr2dnZUZs2bWj27NnCfhkZGTRw4ECysrIia2trOnDgQKm2\nERFFR0cLCb+IiO7fv08dO3akNm3a0Jw5c8rl/Fnp7rXivk8OGzaMbG1tyc7OjpycnOjo0aPCtqys\nLBo6dCjZ2NiQjY0NLVq0qGJPjr21970eivtcJpVKafLkydS6dWuysbGhyZMnk1QqrdgTZCUKCQlR\nSFZJ9G/SwGPHjpGtrS0NGjSIunTpQrGxsTRp0iQ6fvw45eXlka+vr5CksVOnTuTr60v9+vUrk9VJ\nrK2tycnJiby8vITPX48fP6YuXbqQi4sLnThxgoiIDh8+TO7u7mRubi4k15SvGuLi4kKhoaFKdauq\nJyEhgbp27UrOzs60fv16pWPWr19Pjo6O1KxZMyHpo6o+FrRo0SJyd3cXksUXVSZfDSU1NZUCAgLI\n1dWVNm7cWGTZsWPH6MiRI0REFBwcLKyoERcXV2RZUS5evEhisVhYEWP//v1ERLRlyxZydXWlnj17\nCkk1J0yYQJaWluTg4CB8H/jvf/9LHh4e5OLiIqxcVtIYDBo0iBo0aEBubm5Knw127NhBdevWFfpz\n8eLFIvsoV57jNmnSJCH58cSJE8nDw0Nh9ZrCZdHR0UqrGoaHh5O3tzd16dJF+P3m6NGj5OjoSK6u\nrjRt2jQiIvr777/JwcGBPD09adiwYUqrsNy/f586depEvXv3Jh8fnyLvUSKiI0eOUPv27YVju3bt\nSh4eHuTh4SGsGPU+RESc4YgxxhhjjDHGGFNn+/btQ+3ateHj41Op/fjzzz9x584dTJ06tVzq5yAG\nY4wxxhhjjDHG3tu+ffuwYsUKHDx4sNhX898HBzEYY4wxxhhjjDGmFqpVYk/GGGOMMcYYY4ypLw5i\nMMYYY4wxxhhjTC1wEIMxxhhjjDHGGGNqgYMYjDHGGGOMMcYYUwscxGCMMcYYY4wxxpha4CAGY4wx\nxhhjjDHG1AIHMRhjjDHGGGOMMaYWOIjBGGOMMcYYY4wxtcBBDMYYY4wxxhhjjKkFDmIwxhhjjDHG\nGGNMLXAQgzHGGGOMMcYYY2qBgxiMMcYYY4wxxhhTCxzEYIwxxhhjjDHGmFrgIAZjjDHGGGOMMcbU\nAgcxGGOMMcYYY4wxphY4iMEYY4wxxhhjjDG1wEEMxhhjjDHGGGOMqQUOYjDGGGOMMcYYY0wtcBCD\nMcYYY4wxxhhjaoGDGIwxxhhjjDHGGFMLHMRgjDHGGGOMMcaYWuAgBmOMMcYYY4wxxtQCBzEYY4wx\nxhhjjDGmFjiIwRhjjDHGGGOMMbXAQQzGGGOMMcYYY4ypBQ5iMMYYY4wxxhhjTC1wEIMxxhhjjDHG\nGGNqgYMYjDHGGGOMMcYYUwscxGCMMcYYY4wxxpha4CAGY4wxxhhjjDHG1AIHMRhjjDHGGGOMMaYW\nOIjBGGOMMcYYY4wxtcBBDMYYY4wxxhhjjKkFDmIwxhhjjDHGGGNMLXAQgzHGGGOMMcYYY2qBgxiM\nMcYYY4wxxhhTCxzEYIwxxhhjjDHGmFrgIAZjjDHGGGOMMcbUAgcxGGOMMcYYY4wxphY4iMEYY4wx\nxhhjjDG1wEEMxhhjjDHGGGOMqQUOYjDGGGOMMcYYY0wtcBCDMcYYY4wxxhhjaoGDGIwxxhhjjDHG\nGFMLHMRgjDHGGGOMMcaYWuAgBmOMMcYYY4wxxtQCBzEYY4wxxhhjjDGmFjiIwRhjjDHGGGOMMbXA\nQQzGGGOMMcYYY4ypBQ5iMMYYY4wxxhhjTC3oVHYHKlJCQoLKcgsLiyK3lTUtrfy4kUwm4/bKCM+f\n+rYnVxFzqOljWVlzB/D8qWN7qpTnPGr6eGry/Gn6WFaFuZMrjznU9PHk+Stbmt5eaZTlPFbk+WnK\n3FlYWJSu/TJtlTHGGGOMMcYYY6yccBCDMcZYlRcRoYMxY4wREVGtHiBkjDHGGGOFcBCDMcZYlRYR\noYPp043w8KE2ZszgQAZjjDHGWHVWrT4Jyt/dkSMi5Obm4uXLl8jNza2QPohEIqFtbu/d6tfT0xPa\nkSs8t+WlotqpLu1VZNuaPpaVOXfl1f6XYV/iyo1sxO/+BiLtOGjXyIQ0xQB9Ruug4Yfz4Ny+JpZ6\nLS3zdoHqN39y5dUPTR9PTZ4/TR/LqjJ3cmXdH00fT56/sqXp7ZVWWfWrIs+vus2dxgcxwsPDcf36\ndYwZM0ZpW25uLrS1taGrqws9Pb0K6Y+mBRUquj2ZTIbc3Fzo6+uXS/2MsarDNNUbCXucoK8rgk5N\nKYAagIEUkmw9JOz5FqaW4ZXdRcYYY4wxVsE0Pojh5OQEJycnAMrZU2UyGXR1dSu0PxUVTNDU9rS0\ntJCXl6dyLisSt6e+bWr6WFZWhu+ybjciQgfn1gZCSysCWjVy8e/bjwStGpnQytLDubWBuN08AzY2\nkjJtu6DqMn8V1b6mj6cmz5+mj2Vlz51cefVD08eT54/bK0tl3Z+KPL/qMndV8xkexhhj1VZEhA5m\nzDCGLuWhriwHeXk5kGZnQ5qdBQCQyPLQsI4xauhxjgzGGGOMseqGgxiMMcaqlFWrxMjNFUE7PQHG\nGSLIcl5DkpcDaW4epHm5EEEEcwNziMWE3FwRVq0SV3aXGWOMMcZYBeEgRhW0bt06ZGdnv/Vxu3fv\nRmJiYjn0iDHGKs7EiRnQ0yOkp4ugLRPBNEcfUlH+q2q5ua9hbtAAulq6yMgQQU+PMHFiRiX3mDHG\nGGOMVRQOYlRB69evLzKIIZVKizxu7969SEpKKq9uMcZYhbCxkWD+7OeQ5EiRLakF07waEAGQiQiQ\nEepIaiIjQwSJBFi4MLVcc2IwxhhjjLGqpVq9SFx4KZjCy3RWhMKrd2RlZWHMmDF4+vQpZDIZevXq\nhaSkJAwaNAi1a9fG77//jpYtW2Lo0KE4d+4cFixYgAsXLiA4OBivX7+Gk5MTFi9ejKNHj+LmzZsY\nP348atSogUOHDiE6OhqzZ89GZmYmTE1NsWLFCpiZmeHGjRv48ssvIRKJ0LlzZ4SEhODMmTPo378/\n5syZg7Zt2wIA+vXrh/nz58PW1vadz688iEQipbnkJVbVs72KbFvTx7Kyl7oq6/ab1IjEp212YUPM\ndIgM66BO7gMk1chG/Uw9pCVkoUZDERYvToONjQzlEY+vbvMnx0usqkd7ReElVqt+eyXhJTqrdnsl\n4fmr2u2VFi+xWvXaK0zjgxjFLbFa0IVPhpVL++4btxS7PSQkBObm5ti6dSsAIC0tDbt378bevXth\namoKID/Q4eDggFmzZgEAWrZsicmTJwMAJkyYgODgYPTq1QubNm3Ct99+C3t7e+Tl5eGbb77Bpk2b\nUKdOHRw4cACLFy/G8uXLMWXKFCxZsgROTk5YsGCB0Jf//Oc/2LNnD9q2bYsHDx4gJyfnrQIYjDFW\nVtKio9DUMBbTA89hzbkhqK9tCuRFocZzQKIlfRPA4CcwGGOMMcaqG40PYhS3xGpFLz+qqs3WrVtj\nzpw5mD9/Pvz8/ODs7Kx0jLa2NgICAoT/X7x4ET///DOys7ORkpKCVq1awd/fX+GYBw8e4N69e/jw\nww8B5J97/fr1kZqaioyMDGFM+vXrh1OnTgEAevfujR9//BHffvstdu/ejcGDB7/3+ZUHIuIlVjWs\nvYpsU9PHUlOWWE2NjgYAOHQ2wcKeKZgxwwQmkjbIkUVjlM1KtLL+FjJZ+f8VoLrMX0W1r+njqcnz\np+ljWdlzJ8dLdKpHe0Xh+VOP9krCS6xW3fbkND6IUVolPTFRXqysrHD8+HGcOXMGS5YsgYeHh9I+\n+vr60NbWBgC8fv0aM2fOxJ9//omGDRti2bJlyMnJUTqGiGBtbY3Dhw8rlKemphbZl5o1a8LT0xMn\nTpzA4cOHcezYsfc8O8YYe3skkyH9/n0AgGGLlqhrKsHixWn48UcDeJn+isZ6DxB//Bga9QwooSbG\nGGOMMaZpSgxi/PTTT/jrr79gbGyMZcuWAQD27NmD06dPw8jICADw0UcfwdHREQDwxx9/4MyZM9DS\n0sInn3yC9u3bK9X57NkzrFy5Eunp6WjevDkmTJgAHR0d5OXlYc2aNYiJiYGhoSGCgoJQv3593L17\nF+vXr4eOjg4mTZqEBg0aIDMzEytWrMDMmTMr/Z2c95GYmAgTExMMGDAARkZG2LlzJ8RiMTIyMoTX\nSQqSByxMTU2RmZmJo0ePCk9pGBgYICMjP0u/lZUVkpOTER4eDicnJ+Tl5SEmJgatWrWCWCzGX3/9\nBUdHRxw8eFCh/sDAQIwYMQKdOnWCiYlJOZ89Y4wpy0pIgDQ7C3qmptB/833QxkaCtWtTce3LF3j9\nHIjbuxv1XN2gX7t2JfeWMcYYY4xVpBKDGN7e3ujevTv+97//KZQHBASgT58+CmVPnjzBxYsXsXz5\ncrx69Qpz587Fjz/+qBRk2LZtGwICAuDu7o5ff/0VZ86cgb+/P86cOQMDAwOsXr0aFy5cwPbt2zF5\n8mQcOXIEM2bMwPPnzxEcHIxhw4Zh3759+OCDD9Q6gAEAd+/exbx58yASiaCrq4uFCxfi+vXrGDJk\nCMzMzPD7778r7G9sbIzAwED4+vqiXr16sLe3F7YNHjwYX331lZDYc+3atfjuu++QlpYGqVSKTz/9\nFK1atcLSpUsxbdo0iEQiuLq6wtDQUKjDzs4OYrFYeA2FMcYqWubjRwAAw+ZWyhsL5GOWZGZyEIMx\nxhhjrJopMYhhY2ODZ8+elaqya9euwc3NDbq6uqhfvz7Mzc1x//59WFtbC/sQEe7cuYNJkyYByA+S\n7N27F/7+/ggPD8egQYMAAC4uLtiwYQOICNra2sjJyUFOTg60tbWRmJiIly9fakTSSW9vb3h7eyuU\n2dvbY+TIkcL/o9+8Gy43ffp0TJ8+XamugIAAhdwZbdu2xf79+5X2a9WqlZAHY82aNQqBkMTERMhk\nMnh5eb3T+TDG2PvKeZ7/M6dG/fpK2ySZmQW+zqiwPjHGGGOMsarhnXNinDhxAmfPnkXz5s0xbNgw\niMViJCcno2XLlsI+pqamSE5OVjguPT0dtWrVEnI8FNwnOTkZderUAZCfzLJWrVpIT0/HBx98gP/9\n73/Q09PD+PHjsXXrVvznP/8psY+nTp0SfllftGgRLCwsFLa/fPkSurq6AACxWPyOI6F+Tpw4gRUr\nVkAikaBx48b4+eefIRaLsXPnTsydOxfz588XXhWqivT19YXrRK7w3DL1w3Oo3spy/uIz8gMV5i1b\nKtUryc4WvjbS0+PrpozxeKo3nj/1x3Oo3nj+NAPPY9X3TkEMf39/DBw4EACwe/dubNmyBZ9//nmZ\ndqygZs2aYf78+QCAiIgImJiYgIiwYsUKaGtrY9iwYSrzN/j5+cHPz0/4f0JCgsL2nJwc6OvrCzko\nqotu3bqhW7duCmUZGRno3bs3evfuLfy/qpI/lSNnYWGhNLflRf76UkVl4tX09uQqYg41fSwra+6A\nsp+/5EdxAIDXunpCvfLzq2lmhuynTwEASY8eQWRZPtdNdZo/ufK8DzV9PDV5/jR9LKvC3MmVxxxq\n+njy/JUtTW+vNMpyHivy/DRl7kobQHqnhBImJibQ0tKClpYWfH198eDBAwD5T1W8fPlS2C85OVkp\nOaWhoSGysrIglUqV9il4vFQqRVZWlkK+BiLC/v37MXDgQPz+++8YOnQo/Pz8eBUNxhjTIK/fvE6i\nX6+e0rbW4yYIXxd8tYQxxhhjjFUP7xTEePXqlfD11atX0bhxYwCAk5MTLl68iLy8PDx79gxPnz5F\nixYtFI4ViUSwtbXF5cuXAQChoaFwcnICAHTo0AGhoaEAgMuXL8PW1hYi0b9Z3MLCwuDg4ACxWIyc\nnByIRCKIRCKVS4wyxhhTP7mpqchNToaWvj5q1KmrtL1Ww0ZoOiA/d5KkCj8xxhhjjDHGykeJr5Os\nXLkSERERSE9Px9ixYzF48GDcuXMHDx8+hEgkQr169TB69GgAQOPGjeHq6oopU6ZAS0sLo0aNEh41\nWbhwIcaMGQNTU1MMGTIEK1euxK5du2BpaQkfHx8AgI+PD9asWYMJEyZALBYjKChI6EdOTg7CwsLw\n9ddfAwB69eqFhQsXCsuuMsYYUz85r5Ihy8lBTfMGAIDkv/8CABhatYDoTe6kwnQMDAAAeRzEYIwx\nxhirdkRERJXdiYrCOTE0g3ze5Dgnhvq2J8c5MdSvvYLedf5e/XMLEcuXQqStjY4rVwMyGa4GTQCI\n0OSD/mjcp5+wb8Hze3HtKu79tAamjh3QZkL5BLGr0/zJcU4M9WlPFc6JoR7tFYdzKlT99orD81f1\n2ysNzolRue2VNifGO69Ooo7kgy1X8FWViiJvUx47evz4MYYPH44zZ86US3vOzs44duyYUm6SshYU\nFAQ/Pz8hMWh5xsZEIpHSXBb+f3mpqHaqS3sV2bamj2Vlzt27ti9/6oKkUkjS05Gb/BIggkhHB426\n91Sos+DXurXyn8SQ5eQI5dKc19DWr/E+p6Cgus2fXHn1Q9PHU5PnT9PHsqrMnVxZ90fTx5Pnr2xp\nenulVVb9qsjzq25zVzWvnDIUHh6OtWvXVnY3NJpEIqnsLjDG1FDW48fC17LcHGQ9zf/Lh5mnF7Rr\nFB2Q0NLXAwBI3+RDenLsT1wc/Sle3bldjr1ljDHGGGNVgcY/ieHk5CQkDi38uEtlvEmjqk2JRILx\n48fjn3/+gbW1NVatWoXo6GjMnj0bmZmZMDU1xYoVK2BmZoaBAwfCwcEBFy9eRGpqKpYtWwZnZ2dI\npVLMnz8foaGh0NLSQmBgIEaOHAkA2LBhA4KDgyGRSLB27Vq0aNECy5Ytw6NHj/Do0SPEx8fj+++/\nx19//YWQkBCYm5tj06ZN0NXVxYoVKxAcHIzXr1/DyckJixcvhkgkwsCBA2FjY4Nr166hb9++Cue3\nZMkSJCQkYNmyZdAu4p329x3DwnNZ0Y+hcXvq26amj2VlPZL5tu2STIbMJ/8GMSTZr5H15vHNmubm\nRdYnk8kg0tXN/zonBzKZDLG7dgAAYnZuh8Oc+e/S/SJVl/mrqPY1fTw1ef40fSwre+7kyqsfmj6e\nPH/cXlkq6/5U5PlVl7nT+CBGaY1YdrZc6t30RecS93nw4AGWLVuGjh07YsqUKdi0aROOHTuGjRs3\nok6dOjh48CAWL16M5cuXA8gPehw9ehSnT5/G8uXLsXv3bmzbtg2PHz/GyZMnoaOjo7CCjKmpKU6c\nOIFNmzbhl19+wdKlSwEAcXFx2Lt3L6KiotCnTx+sW7cO33zzDUaNGoXTp0+je/fuGDFiBCZPngwA\nmDBhAoKDg+Hv7w8AyMvLE5a3lSdhnTt3LjIyMrBixYpKeV2HMaYespMSIX39Wvh//pMYTwEANRs0\nKPZYLb38nDjSXMWVqUQijX+4kDHGGGOs2uMgRhVgYWGBjh07AgD69++P1atX4969e/jPf/4DID/C\nVb9+fWH/nj17AgDs7Ozw5MkTAMD58+fx8ccfQ0cnf0pr164t7N+jRw9hf3nQAQC6dOkCXV1dtGnT\nBjKZDF26dAEAtG7dGo/fPOZ98eJF/Pzzz8jOzkZKSgpatWolBDH69OmjcB4rV66Eo6MjlixZUkYj\nwxjTVCmFXv2Q5uYi+83rJDUbFJ/USVsv/3USWU6uQrmoir5byxhjjDHGyg4HMd4ozRMT5aXwEwti\nsRjW1tY4fPiwyv313nyA19bWLlU+CvlKHtra2pBKpUrlWlpa0NHREfqhpaUFqVSK169fY+bMmfjz\nzz/RsGFDLFu2DDk5//7ls1atWgrttG/fHrdu3cKrV68UgiiMMVZYym3FIEZuyivkpaZCS08P+iUk\nItbSV/0kBrT46S/GGGOMMU1XrYIYVXF1EgCIj49HeHg4nJyccODAATg6OmLHjh1CWV5eHmJiYtCq\nVasi6/X09MTWrVvh5uYmvE7yvoEEecDC1NQUmZmZOHr0KAICAorc39vbG97e3hg+fDh27NgBsVj8\nXu0XhVcn0Zz2KrJtTR/LSs8S/RbtyyQSpN6NBACYtndA8o2/kRUXByA/H4a2jvKPJoXVSd4k/ZTl\n5kJWILBKeRK1zCheGe0VhVcnUY/2isKrk1T99krCq1tU7fZKwvNXtdsrLXX8LFHd5q5qXjllSB1W\nJ7GyssLmzZvh5eWF1NRUjBw5EmvXrsWCBQvg5+cHf39/hIeHF1tHYGAgGjZsCD8/P/hVtUEwAAAg\nAElEQVT5+eHAgQPv3S9jY2MEBgbC19cXgYGBsLe3L/GY3r17IzAwECNGjEB2dvZ794ExpnnS7kdD\nlpODWo0aoUZ9MwBAhjyIUcKrJADyE3uKRCCJBDnJyUJ5Xnpa+XSYMcYYY0xNREToYMwYY0REaO7z\nCiKqjCU6KknCm8z3cjk5OdDX14dYLEZGRkYl9Yq9Lfm8yVlYWCjNbXmRRx0rKhOvprcnVxFzqOlj\nWVlzB7z9/MXt24snRw7Dolt3aOnq4smRf1+da9y3H5r06690TOHzu/Tf0ZC9fg3LjwIRu3OHfCe4\nrdtQJrkxqtP8yZXnfajp46nJ86fpY1kV5k6uPOZQ08eT569saXp7pVGW81iR5ydv6/ZtLcyYYYzc\nXBH09AgLF6bCxqbk9APv2l5Zn5uFRcl/zAKqwZMYjDHGqhZ5PgwT27ZCfgu50jyJAfyb3DPpbNi/\nhTIZZHl5ZdNJxhhjjDE1EhGhgxkzjKGjA9SvL4OODjBjhmY+kcFBDMYYYxWGZDJkPn4EADCybiUE\nI+QKLq+alpWL7SEP8CLtNQrTenNcVnw8RDo6gPwvAjk5SvsyxhhjjGmyiAgdTJ9uBB0dQCzOf9FC\nLCaNDWRwEIMxxliFyUtLA0ml0BEbQltfH1p6hZ7EMDMXvt586j6C/4rH6oMR2BX6ALvDHgjbtAs8\nwVHbzh76bxIZS3MVl11ljDHGGNNk/wYwCGIxgWQyIU+YpgYyOIjBGGPsrRARkm/8DUlmpvD/+BPH\n8PzSxRKPzU15BQBC0KHg6yT6deoKwQkZEa5HvwAAxD3LwJ/XHuPo1cd4/Dy/zYLBj3ourtDSzX8y\nQ1Z42VXGGGOMMQ317ysk+QGM3JRXSLsbifSYGEhf5z/JqomBDM04i1Kqqkuscntv3wYvsaoZ7VVk\n25o+lhXZ3pPjfyJ25w7U7dgJbcZPxMMTx/Fw105o16oFM3ePYo/NS0kBAOiZ1oaWlhZ0CgQxalk0\nEM7j/pNUlcdfvvsMTc2soK2fH7TQrlEDdRwc8eRofnLQslpmVZPnrzi8xKp6tFcUXmK16rdXEl6i\ns2q3VxKev6rdXmmp0xKrq1cbIjdXBBPDPKRF3YckKwsAoF2zJkAyyH/dNTQkJCVpYfVqQ6xdq/oz\n1tuo7LmrmldOGVKHJVYZY0ydPD58CADw4tpVpERG4MYvPwEApFlZIKm02GNzXr15EsPEFIDiayE1\nzf/Nh3Et6jkAoFuHRgj6oC1c2tQHAFyKfAYZkfAER50OTtDW04P2myczZLk5uL91M27On1NiXxhj\njDHG1NmkSZnQ05Uh8W48JFlZEGlpwaBxExi3ag2dWrWE/dLTRdDTy99fE2j8kxhOTk5wcnICoLwE\nTGmfFph2bhpuPr9Z5Hb7evZY4rmkVHUVbrNhw4bo378/Vq9eDQCQSCRwcHCAg4MDtmzZUqo6C9q9\nezfmzZuHBg0aIDMzE02bNsXkyZPRsWPHt67rbQwcOBDffvst7O3ty7UdIH8MC89lRS/NxO2pb5ua\nPpbl3Z4kOxuSAktS/7NogcL23MxM6IrFRR6fk5wMANA1MYZMJkMNi4bCthoNLCCTySAjwrV7zwAA\nHa3rooWFEdpb1cH9+FS8SMvB3UevYNCoCVJu34aZVxfIZDIh0ackJwdPTwUDANJiHsDQqsV7na+m\nzV9lt6/p46nJ86fpY1nZcydXXv3Q9PHk+eP2ylJZ96c8z69161wEBRzG3B/bQCqqBbPWFtARGwIA\n5L92ZmSIIJEACxemoHVrCcqyO5U1dxr/JEZZsDG1gbZIG+YG5kr/tEXasDG1eee6a9Wqhbt37yI7\nOxsAcPbsWZibm5dwVPH69OmDkydP4sKFCxg3bhw+++wzREdHK+0nkZT9msGMMc31Ivwabs35XuU2\nXcP8H5jSN9/LipL9NH/t9Rr18p+s0K9dG22/mgkz7y6o5+wMAIhNTEdyRi5MxXpo3iC/Xi2RCK5t\nzADkP43RpP8AdFz+I4xatszfrifPifFvYk+qYh+KGGOMMcbKmln2FXxq8yOgb4DXMFTY9m8AIxU2\nNprzu1+JQYyffvoJn376Kb744guhbOvWrQgKCsKXX36JH374AZlvkrs9e/YMQ4YMwdSpUzF16lT8\n+uuvKuvMyMjA3LlzMXHiRMydOxcZb/6qR0TYsGEDJkyYgC+//BIxMTEAgISEBEyfPh1ffvkloqKi\nAABSqRRz585FTgUsp9fXqi90tHSQJ81TKM+T5kFHSwf9WvR7r/p9fHxw+vRpAMCBAwfQr9+/9f39\n99/o3bs3/P390adPH9y/fx8A8Ouvv2LKlCkAgMjISPj4+AiBkILc3d0xZMgQbNu2DUD+ExPfffcd\nevTogfXr1+PkyZPo1asX/P398eGHH+L58/xHuH19fZGamgoigq2tLfbu3QsAmDhxIs6ePYvs7Gz8\n97//hZeXF0aNGoXXr/9dAvHAgQPw9fWFj48P5s+fDwA4fPgwvv/+ewDA+vXr4erqCgCIi4tD3759\nAQDOzs5YunQpunXrBl9fX+FcGWOVT5qTg3v/W43sxKcAgDpOHWFsY4MaZmbwWrwUuiYmAABJdlax\n9WQ8fAgAMGjaDGlZudh34SEkDZqhxfBPoFPLAABwKyb/aQ2HFnWhVSB3UadW9QAAEY9SINLSgq6R\nkbBNHsQoGETh10kYY4wxpokkmZmQZGcjPTYGGXEP0dQwFktX5UEiESEjI/+zk6YGMIBSBDG8vb0x\nc+ZMhTI7OzssW7YMS5cuRYMGDfDHH38I28zNzfHD/9k77/CoqvSPf6bPJJMy6YUkkAaEDqGKoIgU\nFwULwrquq2tdXREL67qWtawiiwJiXbGtZbH+BFRAQBQEJSAdQgklpPdJJjOZPvP7YzI3mTSSkIQQ\n7ud5eJi599zznntOZube733L4sUsXryYu+66q8k+V61axaBBg1i+fDmDBg1i1apVgOeGvaioiOXL\nl3PXXXfxzjvvALBx40Zuu+02HnvsMdas8cRib9iwgUsvvRSVStWkjY5Ep9ZxXfJ1VForfbZXWiu5\nLvk6glXB59T/zJkzWb16NRaLhSNHjjBs2DBhX3JyMl9//TUbNmzgkUceYdGiRQDccccdZGdns27d\nOh566CEWLVqERqNpsv9BgwZx8mRdaUK73c66deu45557GDVqFN988w0bNmxg5syZvPGGJ7Y9PT2d\nXbt2cezYMRISEti5cycAu3fvJj09nQ8//BCNRsOWLVt4+OGHOXDgAABFRUU8//zzfP7552zYsIF9\n+/axfv16Ro8eLfSRkZGBTqejsLCQjIwMxowZI4wtJCSE77//nj/+8Y+89dZb5zSvIiIiHYf+gG9I\nXcINNzJwwd8Z8eJiIoYORa7xxF06a+pEBJfd7iMk2A0GrOVlSJVK/KKj+WFvAd/syOHhFTtxuepC\n7Q6e8eTNGNRb52MzQuf5jjPUNC6j6q1WYq+uFrY5zuIVIiIiIiIiIiJyIeG0WMj+/DMy/voXMu69\nmwPPPo29shKZWs2w8UEsXFiFwwElJdIeK2BAK0SMtLQ0tA3im4cMGYJMJgMgNTWVitoY59aya9cu\nJk6cCMDEiRPZtWsX4EnCOWHCBCQSCampqZhMJvR6PTKZDKvVitVqRS6XYzKZ2L17NxMmTGiT3XOh\noTdGR3lhgGeO8/LyWL16NZMmTfLZZzAYuPvuu5k0aRLPPPMMx44dAzwZYZcuXcq8efMYM2ZMizkv\nGubhuOaaa4TXhYWF3HTTTVxxxRW8+eabgqfL6NGjycjIYMeOHdxyyy0cOXKEwsJCgoOD8fPzIyMj\ng+uuu04Yf//+/QHYv38/Y8eOJTQ0FLlcznXXXceOHTuIiIjAZDJhNBopLCxk1qxZZGRksHPnTkaN\nGiWMZ/r06YBHKMvNzW3vlIqIiHQwppwzwmuJTIYmMtJnv6xWRPV6YjhqTPz2yEPse/opqk95RNSC\nDd8DEJiSikQm40xJXW6NkioLNruTBe/s5FRhNQq5lH5xvgKxWiFDIZditbuw2n29LLzVSuwGg7Dt\nbKEtIiIiIiIiIiIXCi67jcxXlpK/7jthm9zfH//4eOJnXYdEKiUtzcHChVUkJDh6rIABHZDYc/Pm\nzYwbN054X1JSwt/+9jc0Gg1z584Vbm7rU1VVhU7necIWHBxMVZWnzEtFRQVhYWFCu9DQUCoqKpg2\nbRqvvfYadrudu+66i6+++oprr732rKVdNm3axKZNmwB48cUXiYmJ8dlfXl6OQqEAaCTUNESr1TJ3\nwFz+l/k/IpWRlFvLuWnATfQK7dXicWdDIpGg1WqZMWMGzz33HN999x0VFRXI5XK0Wi3Lli3j8ssv\n57PPPuPMmTPMmDFDGGthYSFarZby8nJhm1qtRqFQ+JzP8ePHBTFKJpMRGhoq7H/66ae57777uOqq\nq/j555958cUX0Wq1TJo0iY8++oji4mKefPJJNm7cyKZNmxg/fjxarRa5XI5GoxH6kUqlaDSaRvZV\nKhVKpRKtVsuYMWNYtWoVffv25bLLLuPjjz9m7969LFq0CK1Wi1QqJSQkBK1WKxzf1LqoVCpCQ0N9\ntjVcW5ELD3ENuzd5taF7EUOHMey++wlssF4BoaHogUCVipiYGHJ+3IzdUIXdUMXBhc9z9f8+4+Ch\ngwAMueVWImJisDgOC8cH6UKorLFRWuUJTRuaHEli77hG49AFqCnR1/DS/2Xy2vwpQlnnMl0IhYCi\nXq4frUrZ5N9VdV4eFr2e8EGDfLa7XS6cNityddNebRcD4ufwwkZcvwsfcQ0vbMT16xm0dh3tJiMn\nVq+m95SpaOrdw3YGbpeLHS/8C8PRI0iVSlJmziJs4CCiRqQjrb2f9RITA5MnA/g12VdP4JxEjP/7\nv/9DJpNx6aWXAqDT6XjjjTcICAjg1KlTLF68mJdffhk/v+YnUCKRCBehzREWFibkUygqKqK8vJzY\n2FheffVVHA4Hc+bMafKPbfLkyUz2rCDgya1RH6vVikqlQqvVCnk5WmJ6r+l8evhTDFYDUreUq+Ku\natVxLeF2uzEajVx77bWo1WoSEhLIz8/H4XBgNBqpqKhAp9NhNBr54IMPcLlcGI1GDAYDCxYs4Msv\nv+SJJ57g008/ZcaMGVgsFux2uzCuX3/9lffff58vvvgCo9GI0+nEbDYL+/V6PcHBwRiNRj788EOc\nTidGo5Hg4GBKS0uxWCyEh4czfPhwXnnlFZ5//nmMRiMjRoxg5cqVjBgxgqNHj3L48GHMZjP9+vVj\nwYIF5OTkEBQUxGeffcaf//xnjEYjw4cP56WXXuLBBx8kKSmJLVu2oFarkclkGI1GXC4XJpMJlUqF\n2WwWxtIQr1eOl5iYmEZr21l4hbOuysTb0+156Yo17Olz2dn2KvPzAQi7fBJGuRxjvfWKiYnBG+BR\nVlCAoqCAUz/9JOx3Oxyc2ruHmvIyAGpUKgoKCsgvrfOayC8o5nRRXSjIVSOifP4mvOenknt+L7Ly\n9Bw4eorwII/gUFOb0LOquEg4pqKoqNHfldvtZs/f/4a1opz0l5eiDKrz9sj+4nPy137L0GefJyAh\nAeg569caOvNz2NM+D+fbXlN01vr19LnsDmvnpTPWsKfPp7h+HUtPt9ca2rKOB/71LNUnT1B87Bip\nd9/TaH9Hnl/Zrp3k/bwVmUbDoMcexz8uHoCi2nyGPWXtWisgtbs6yU8//cTu3buZN2+eIEIoFAoC\najPUJyYmEhkZSWFhYaNjg4KC0Os9Mc96vZ7A2uRsISEhlJWVCe3Ky8sJCQnxOXblypXMnTuXdevW\nccUVV3DzzTfz5Zdftvc02oQ3N0ZedV6H5MKoT0xMDLfffnuj7X/5y19YuHAhU6ZM8akm8vTTT3Pr\nrbeSlJTESy+9xMKFC4W5W7NmDVdeeSXjx4/n1VdfZcWKFaTUZvBvyMMPP8zdd9/NtGnTGs31sGHD\nSExMBGDUqFEUFRUJYSu33HILJpOJiRMn8tJLLzF48GAAIiMj+cc//sHs2bO58sorGTx4MFOnTgU8\nISoFBQWMHj0amUxGTEyMTyiJiIhI98VW6fnOVup0Te735sRwmM24XS70hzx5cvwTegNgLijwlGaV\nSFAEBGCyOKg21yVLttmd5Jd7QlF+f1kifaJ8s2t7MdY7xmKrCymRNhlOUpdw2Iu5oABLaQlupxNr\nuW8oZP7abwHI/WZ1k7ZFRERERERERMBzvVN90lOEwBs221m4XS4Kf/BEF8TNvFYQMC5m2uWJsW/f\nPlavXs0zzzzjk1jTYDAIYQHFxcUUFhYS2SBuGjxJI7ds2cKsWbPYsmWLcGOcnp7O+vXrueSSS8jK\nysLPz08IOwHIzMxEp9MRHR2N1WoVvDi6okKJl5lJM8mpzumQXBhAk6VPx40bJ4TopKens23bNmHf\no48+CsCSJUuEbbGxsWzfvh2AOXPmMGfOnGbtNRR8pk6dKogMDXn11VeF1yNHjiQvL094r9FoePPN\nN5s8btasWT4VVrz07t2b/NqnueARpOqTkZEhvB4yZEiXiVMiIiJnx1YrPCuDmxYxhJwYNSaqT57E\nYTSiDo9AN2QIpjPZwg+9IiAAiVTK8Xy9z/FWh4uCck+lq9hQ/2bHUWWqS+ppstQJu7ImE3s2rpRS\nefhQ3X5jdaP9AA7TuXnYiYiIiIiIiPRsjPWEi4bhHB1N3tpvMRw7ilSpJHzM2E61daFwVhFj2bJl\nZGZmUl1dzT333MONN97I119/jcPh4LnnngMgJSWFu+66i8zMTD7//HNkMhlSqZQ777xTyGnw1ltv\nceWVV5KUlMSsWbNYunQpmzdvJjw8nAcffBDwPPnfs2cP8+bNQ6lUcu+99wrjcLvdfPXVV0LbyZMn\n8+qrr+J0Ornjjjs6fGKaQ6fW8dSYp7rMnoiIiMj5xmmx4DSbkcgVyJvJH+T10LCWl6M/sA8A3ZAh\naCKjAKg6egQARWAQAIeyG4gY9TwxYsOaD0FMTw1n5zGP62SNtU7E8JZYtRuq6sbdRGLP+iJGfcHD\nVc/Trf72s+Gy26kpyKcy8zCl27cTdcVkoi+fdPYDRURERERERC5IbFWVlP76i/DeUl6G2+0+a4qE\n9uCoMVGwfh0AqXfdgzIoqMNtXIicVcSYP39+o20NK2h4GTNmjE+5zPrcc09dnFBAQABPPdVYCJBI\nJM0KEhKJhCeffFJ436tXL6HcqIiIiIhI52GpjbdUhYY0+wOtifKIFZbiIixFnrwUusFDUEdGIpHJ\nsNaGuylqwwcP15ZRjdRpKNabKa2yYLI48FPJCfZXNjuWW65IFkSM+p4Y/nGeJKAue124SUMRw2W3\nC2IKgL2eJ4altKTR+baE02Kh+uQJSrZv87mQKd+ZIYoYIiIiIiIiPQSXw0HJ9p/JX7cWuZ8/MVdO\n4fg7b0O9XBAui4XMJS/R/4EHkcrPuW6GD6c/XYnDZCKwb19Cho/o0L4vZDp2lrs5DauZdIZadja8\nNhuWPRXttc1Gw7U8W6WajqKr7Fws9rrSdk+fy86wV7F/Hyc+/IDg/mmAR6hozo5ftCcRkyknxzMe\npQpd/zSkSiWpd93DsTdfB0AZFER5tZUivRk/lYz+ccEU681CUs/YMD+hhHdT5xfor2LK8Fg27MnH\nbHPWbU9MInzsOB9BwVFT4zNew6mTuGx14Sg1ublkLnsZU06OEC4DnosRt82GTK1udm6yV68if/3a\nuvGpVLisVlx2W7vW4nx+9urTWePoCZ+H7mSvOTpjHD19LrvL2nnp6PH09PkU169j6en26uO02ajY\nuwfjmWwCEpPQDR6CrNar0zsuU34+ma8swVJcLBx3/O23AAjqn0bEuEso3LwJ4+nTVB46yMn330UT\nE4NfVDRhI0chlUpx2e1Im7iuaQ36gwcp+XkrEoWClFtvb/L6yMvFtHZwEYgYv/32G7t37+buu+8+\n30MRERERuaAo+20X1rIyin/eCoAmonGOIy8Kf3/kWq0neScQPGCAEOIRMWYsjupqTq38hKDUvkIo\nSVq8Do3S84PsFTF6tZAPw4uf2vPTVd8TA6DPnN9TsXcPTosnoWfDsBBvKInczw9HTQ0l27fRHLaq\nKjQtiBj1w1IAhjz+JHufegJnF+ZoEhEREREREWk79upq9j//LOZ6BShkGg0xU6YScsutABRt+Yms\n994BPA9xoi6bRPYXn+F2OpH7+zPwoUeQKpUEpfalePvP5K9fT8kv24X+xr39LvpjRzm05CX6zP09\nvaZdRf6G9ZTv3k3/v85DEdB0AnOXw0HZzgyC0waQ9b7HfsKsa/ETy/f60ONFjPT0dNLT04HGJWDa\n4y2QmSln+XIt8+YZSUtznP2ABnSVR0RPtud2uxutZVeXZhLtXbg2e/pcdqQ9S71qUQCqiIhm+3e5\nXGgio6g2ehJ4Bg8c6NM26orJhI+/FJlKxRdrMgEYkBCM3ujxjPD+HxPq1+I5uFwuQfgwmu0+bRVB\nQfSe+3tOfvA+APZqg8/+6lOnANANGerjsREzdRq9Z8/BeCabE++9S01+Hha9HlV4eJNjcbtcmEuK\nfbZJahOLOq3Wc1qD811mrrPtX8ifh+5oryvt9/S5PN9r56WzxtHT51Ncv55pz2EyYTiRhdvhICA5\n2acseku4XS6qjh3FYTSiCAgkMCUF/cEDSGQydIMGU/jTZsyFhSh1IYSPGYP+wAFq8vPIXb2Ksu3b\nSHv0Mc58/RUAmphYhjz1NDKVCnlgIOW/7SJ22nSQy3G5XKgiIoi/9noCU/tyZPkyweNzz1OPC+G1\np1f+D0dNDbmrVwGw86EHGP7Ci6hCw4Tx1uTn4Rfbi9Mr/0fhpg3Cufj37k3M1OmtXpPusnadTY8X\nMTqSzEw5jz0WhM0m4bHHgli4sKpdQoaIiIjIhYC1ohwAdXgEltISAhKTWmyvjowUqpD49YprtF+m\nUuF2uzmSWwnAwN46Mo765p9oKamnF/9aT4z6iT29RE28nPAx49hxz504TCbcLheSWpdHr4eGpsHT\nDFVYGBKZjIDEJNSRkdTk52GvqmzWvqW0FFc9j4teM65GVlupy2W1NXeYiIiIiIiISCswnMiicNNG\nynfvxu2oy3UVMmw4KXfchdyv6WuFmsJCynZmULbjV8xFhU22kfn5Qe1D18Sb/0jo8BEk3HAjZ776\ngpJtP2MuK2P3gocBkPv7M+y554XriIix44gYO67JfoMHDGT4wn+Tu2YVxVt+EgQML14BA8Bls3Hk\nteUMeeoZCjZ8T/an//PYq+fR6iX5T39G0s5wlJ6MKGK0Eq+AIZdDcLALo7FjhIzY2Fiuu+46oZyp\nw+Fg2LBhDBs2jA8//LDN/X322Wf861//Ijo6GpPJREJCAg8++KBQxnb+/Pns2LEDrVaLxWJh+PDh\n/P3vfyem9qJ+9OjRQkUZp9PJ9OnTeeCBB1C34FYtIiLS83C73djKPSLG4Keexm6owi8mtsVjvJVI\nAPyioptsU2N1YLI4UCtkhAWqUSl8f5hbKq/qxV+lEPpqCplKhdzfH4fJ5HkKU5tM1BvqoQ4L92mv\n0Na5dHqzftsqmxcxTLmevB/BgwaTdMufUAbrhISiTpsYTiIiIiIiItIQt8uFKecMmphYIfcEeJJs\nG/PysOn1VJ/IwnD8OKacM56dEgnaxEQcJhOW4mIq9u7h0KIXiL5yKprISAJTUrGUllK2cwdlOzOE\nvFwAcm0A2j59sJaW+ggazhpPJTRlsI7ggYM8ZqRSes+eQ9Rlkzjw7NPYjdUoQ0JIuH62IGC0BlVI\nCMm3/pnICZdhKS1BHRqGtayUY/95E4DoyVMELwtTdjbGU6cEAQNoJGCEjR6DtnfvVtu/mBBFjFZQ\nX8DQaj3KnVbr7hAhw8/Pj6NHj2I2m9FoNGzdupWoqKizH9gC11xzDc8//zwA27dv58477+SLL74g\nJSUFgCeeeIIZM2bgdrtZsWIFN954I5s3b0ZZ+4XyxRdfEBISgslk4m9/+xuPPvoor7zyyjmNSURE\n5MLCXl2Ny25H7u+PQqtF0Uxp1frUT4QpbybWs8zguckPDVQhkUhQyusuDrRqOYF+Z6+1rlJ6jrHY\nnHXjdbhQ1OtLHhCAw2TCXl1dT8TweGKowsJ8+qsfl+otAWurqqI5vCKGf1ycIIh4kxq7rNZOK7Mm\nIiIiIiJyvrBXVyNVKgXPw7bgdrk49tYblO/aCUDEJeNJuHEuhd+vJ2/dd4JnhIBEQsyUqURPnoK6\n9je7prCAI8uWYsrJ4cS7KwCQafxwmmuEw2QaDaHDRxA2egxB/dOESiHG7GyqT51AqlCiiYpG7ueH\nKjTUR0wBUIeHc/X/PqWgsLDRvrYQkJhIQGIiUqkUd0oKDqsFVWgYuoGDCEhKInf1KsxFhWQuWyIc\n0+f3fyCoX3+kahVOsxlzURFh6SPbPYaezkUlYrSnOklTAoaX9ggZTVXvmDRpEj/88AMzZsxg1apV\nzJo1i4yMDAD27t3LU089hdVqRa1Ws2TJEpKTk3n77bc5evQoS5Ys4ciRI9x333189913jeyNHz+e\nP/zhD3z88cc888wzjcZy1113sX79en788UemTp3qs9/f358XX3yRkSNHotfr0el07Tq/jkasTtJz\n7HWl7Z4+lx1tz66vAEAVGtqqvqVSKSGDh3B65SdoE3o3m0G7otojYoQFqZFKpaiUdT9DsWH+zR5X\nfwyaWk8Mq91TnWTjnjz+9+NJHr1xCP3iPPGyyoBALEVFOExG4ViXxWNb08ATQxkYKLRR1X7P2Q1V\nzZ53TW4uANr4hLo2UikSuRy3w4HE6RSSmraW853l24tYneTCsNccYnWS7m/vbIjVLbq3vbPRU9bP\nVlmJVKVCrtEAnhxZex7/O/7xCQz+xxNtEurdLhcn3n9XEDAASrZv80mure3dB2VQEAFJSQSmpOIf\nH+/jJQmgje3FkCeeIvvLz6k+dYqavFyc5hqkKhWhw4YTPnoMukGDkSoaPwwJTMDAXzEAACAASURB\nVEwkMDGxVeOVqVQoOsgD3TufMZdfIWyLHHcJ6rBwDjz/LA5jNUgkJP/pVqLrtQEI7NO68Ta01VWc\n789ejxcxzqU6SUsChpeO8MiYOXMmS5cuZfLkyRw5coS5c+cKIkZycjJff/01crmcrVu3smjRIlas\nWMEdd9zBDTfcwLp161i+fDmLFi1CU/tF05BBgwbx8ccfN2t/4MCBnDhxopGIARAQEEBcXBynT59u\nlYghIiJy4WOrquLkh/8FEJJOtQa/mBjSFy9p0WvD64kRFui5QFAp6n4Ee4WdPZQEQF0bgmK1e5JJ\nffSDJw/HZ1tO8c+bhwN13hX1K5R4PTHk/n5ChRJoXTiJ02LhxH/fJ2Lc+DpPjPgEnzYypRKHw4HT\nZm2ziCEiIiIiInI+sZSWULBxI8Yz2VQdPYJfrziGP/c8TquVM199idNiwXD8GNUnsghMSW11vxX7\n9lK87WekShUDFzyKraqSE/99H5fNRkCfRGKnTCV0RHqr+lIGBZF6uyfnVe533+AfF0/o8BHt8g45\nnwSlpjLkiadwu8E/Nha5f+uuf0Tq6PEixrlUJ1m+XIvNJiE4uOWsq1qtm5ISKcuXa3nrrebjqJuz\nmZaWRl5eHqtXr2bSpEk++wwGA/Pnz+f06dNIJBLstXHXUqlUED5uvvlmIedFU/bO1SuiLceL1UlE\ne93dZk+fy3O157TZ2PXIg0J2bVVISKv69Lbxhmo0d0xppRmA0AAVLpcLhazuaU7sWSqTePtVyj3H\nWG0On/YapUx4L6sVdR0mEy6XC7fL5TkniQRkcuTaAEHEkPrV2ZXXhp7YKitxuVzC9rwNntJp3vJp\nUoUCdYNqLVKVCmpqcJjNyPzad0FyvjPsi9VJLix7XWm/p8/l+V47L2J1iwvDXnNcqOvndrs59vZ/\nMBw/Jmyrycvl8LIlGI4f9wnZyN+4AXVMLJWHDqIKDW2U9NvtcqE/eIDirVuwlJRQk+fxXoyZNo2A\n5GQAQoaPALcbWW24R1vPT6rRkHDDjcL7jp6fruhPm5TcKfYuls9ejxcxzoV584w89lgQRqOkWU8M\nAKNRglLpZt48Y7NtzsaUKVN49tln+fLLL9Hr9cL2xYsXM27cON59911yc3O54YYbhH2nT5/G39+f\n4uLiproUOHToEMnJyS3uHz9+fJP7jEYjeXl5JLbSBUtEROTCpmTbVkHAAFCGhjZqozda+eiHE0wZ\nHiuEb7SWIr3nQihS5xEZ4sK1hAaqiA7x45IBka3qw5sM1GJ34XLVfTf7qep+0rz5ObzJPL3/S1Uq\nJFKpj4dG/Sc4gidGg5wY9gaeGX6xvRplC5fW9mOt0LfJg0VEREREROR8YsrNEQSMxD/cjL3aSO6a\nVej37wMgMLUvEZeM58QH71GWsYOyjB3Csb1+dzXx19+ARCLB7XZz/D9vUrYzo5GN+mKHRCLxPFQQ\nEWkn3SuQrJuRluZg4cIqHA6PUNEURqMEh4NzrlIyZ84cHnroIfr37++zvbq6Wkj0+fnnnwvbDQYD\nTz75JF999RV6vZ5vv/22yX5//fVXPvnkE/7whz802ud2u3n33XcpLi7msssua7TfZDLx2GOPMXXq\nVIKD23ajIiIicuHhcjjIX7fWZ1tTZczeXneMPSfKefHzA1TX2MktMfDSlweFsI6WKCj3iBjRIZ5+\ng/yVvHznaB65flCjSiXNoVZ6w0mclFfXVQOxO+ueBsjUHpHEW1bVWxLVK1h4nyrJNL7nJyT2NFTh\nrv90oUHsp19cfKNxSfD8Thx84blWnYeIiIiIiMj5xOXw3LsYT54EIHzsOGKnTCPumpkkXD8b3eAh\npN79FwY99jiREyYSfcVk4VhNTCwSmYy8776hYt9e3G43hZs2UrYzA6lSScINN5J4y61Ce7HKhkhH\nInpinAWvkNGUR0ZHCRgAMTEx3H777Y22/+Uvf2H+/Pm88sorXHFFXcKXp59+mltvvZWkpCReeukl\nbrzxRsaMGQPAmjVr2LlzJ2azmfj4eFasWCFUJgH417/+xbJlyzCbzQwfPpwvvvhCqEwCMHv2bCFk\nY9q0acyfP/+czk1EROTCoGxnBtayMjRR0VjKSnE7HPg3uFm3OVwcyanzSrj/zV+RSiW4XG6O5FZy\n86Qkn4Rf9St1WO1Oyg1WZFIJEcHtT5oll0mRSSU4XW72nyoXtleb62rJS9W1YoXFXPu/R8yQqTx2\nE66fzZmvvqDffX/16VuqUAjlWSuPZCLXavGPi8duMPi084ttXG7WUloivHZarRdcjK6IiIiIyMWD\n8Uw2hxcvIrBvP+H3yustIZHJ6DXj6kbH9J7zezQxsfjFxhKU2pfsLz4nf+23lP+2i+KtW9Dv2wtA\n/LXXEzttuqcvwO10ogwSH4iKdByiiNEKmhIyOkrAyMrKarRt3LhxjBs3DvDk9Ni2rS5776OPPgrA\nkiV1JXliY2PZvt0Tpz1nzhzmzJnTrL1ly5a1OB5vQlEREZGLj8KNntrlsVf9juABA7GUFAsXNGUG\nCyt/PMmhM/pGx3lDOpwuNzaHC5VChsXm5J8f7SYm1J95M9OQSCQcyanEDUQEq5HLzs0RUKWQUWN1\n8OP+utrvxnoihhBOYjaTu2aV4EkhqxU3Yq/6HVGTJiFvIneFIigYh8nEoX+/CMC4dz/Apvc9b7/o\n6EbHuZ11JV9tVZVoIloXHiMiIiIiItLVZH/+KQ6TiYo9u4VtDfNbNEQqlxN9eV3+vuC0NPLXfktp\nbb4oAEVgIBGX1IWpR13um+9PRKQjuKhEjPaUWPVSX8goKZGiVLrbJWB0RQnSnm5PLLHac+x1pe2e\nPpfnas/lcAhVNyLGjEGmUqMJq8vr8EtmCbtPlDc6LthfyV+vT+f1//sNvdGGyepEo1KQVaCnuNJC\ncaWFY3kG0hJ0rN+dB8DEQdFtHm/D9mqlR8TIL69LNlZttgvtFLVhIhV792KrrBMgZGpPaVekUmQN\nyrd5UQUHYy7IF947a2qwVvieu39sbIvn4DAYkEY1Fjqa43yXKvMilli9MOw1h1hitfvbOxs9pURn\nT7V3Nrr7+rndbqpPnaR8926qMjN99imCgghKTkbSBpuBiUme3BZuN9qE3vS9516UwcFNhqI2RXdb\nPy8dNa6uPL+L7bPX40WMcymx2hCvkLF8uZZ584znHEIiIiIi0h1wu1wc+8+buJ1OVGHhQshFfern\nngB47d5xSKQSAjQKoqKi+O/a/R4Rw2wnLFDN8by6xJjvfH+Mf98+itIqT0jHyNTwcx5z/fwZo/uF\ns/NoKTUWBy6XG6lUInhi1BcwgCbPrSGK2uSeXsr37MZaVuZrv4nEnX3vuZdjb71Ra7flSlUidVj1\nelxWK5ra/E8iIiIiIh2Hy+FAIpVSsX8fJz/+0Of3LHjAQOKumcmpjz8ifta1bRIwAOT+/iT+/g/Y\njdXEXz1TLC8u0mX0eBHjXEqsNkVamuOsZVRboqs8InqyPbHEas+z15U2e/pctsde6Y5fhUziUqWi\nyT7KDRbh9cwx8Wg1vmXR/NSe99VmGy6Xi8M5deJBWZWFnJJqDDWecA+tRt7uefEep1bUXWhdkhbJ\nvpPlWO0uzDY7GqUcSTMXUlKV6qy2vck9vZz+bCUAvWZcgyosFIU2ADf4Jv4EwkaPoer4cYo2b8Ja\nUdGuczzfZQK7usSqMfs0BxctxO1wMOSfz+Lfq1en2utsevL69fS5PN9r5+VCLdF5sdlrju6wfjWF\nBegP7Memr8RcWEDVkUxc9rpwS0VwMJrISIynTxN12eUEpvZl6LP/8rHTFnvRV05p1zjr013Wz0t3\nL9naXWydD3teeryI0RISiQRnvRhmke6P0+lsUxiQiIhIy7gcDs7835fC+8CU1CbbVdR6Yjz7x+HE\nR2gb7dfWihgmi4NKk41ThdUo5FL6xwVx4LSeU4XV2B0ulHJpq6uQtISqtkJJoJ+CAQk6lHIZVrsL\nu8OFRllXnaQhrUm2qWxQjclZU4NELid68uSzJibzHmururA9MUx5eWR//imhI0YQeenENj+day25\na1bjqk26enrlJ/R/4EFk4pM8ERGR84jDbOb0yk9QhYQQMX4C6rALp2R2xb69HFm+DJp5qBgzbTq9\nZ89BIpXidrk67btdRKSzaZWI8cYbb7Bnzx6CgoJ4+eWXATAajSxdupTS0lLCw8N58MEH0Wq1uN1u\n3n//ffbu3YtKpeLee+8lMTGxUZ+nTp3i9ddfx2azMWzYMG677TYkEkmz/e7YsYPPP/8crVbLggUL\nCAgIoKioiJUrV/Lggw+26+QVCgV2ux273Y7Vaj37AR1AT8xR0ZX2JBIJCoWiU/oWEbkYKfpxM9bS\nUhRBQURdfkWzCbi8IkZIQNMigL/a87k0WRzsO+nJH5EWH0xChJYDp/UczfWElwT5d8wNqlcIGds/\nAplUglLuuRCz2j1PBLzhJA2RtiOcBDxl51qTWV0R4Mmz4TAaz9q2u+J2ucha8R9MOWeoPHgAU04u\nSX+8pcPt2I1G9Af2C++rMg+z759PMPyFRaJYLSIi0uVU7N9P2Y5fsVVVUnXEky+iaPMPpC95Bam8\n+z/3tVVVkfXuO4KA4R+fQNSkKzAXFlLw/TrCRo2mz5zfC+1FAUPkQqZVn8jLLruMadOm8frrrwvb\nVq1axaBBg5g1axarVq1i1apV3Hzzzezdu5eioiKWL19OVlYW77zzDi+88EKjPlesWMHdd99NSkoK\nCxcuZN++fQwbNqzZftevX8/ChQvJyMhg27ZtTJ8+nU8//ZS5c+e2++QlEglKpZLQ0NAuEzG8SVC6\nyvWmp9sTERFpPw6zmdw1qwFI+tNthA4b7rPf7XZjNDuQySRYbE6Ucin+6qZ/NrzhJUaznawCTznS\nYUmhqGs9JrzhJQF+HSNCjkwNo6LayuRhMQAoakUMu6OxiKGOjMRSXFy7vRWeGE2IFTFTprVqXN5k\nZo6amrO07L4Ubf4BU84ZFIFB2A1VlGzbSp+5c5EqOtZDovy3XbidToIHDMRaXo65qBBLURHG7NME\n9Gn88ENERKR16A/sR+bnR2ByyvkeSptwmM04TCYfzwf9wQPYq6oIv2R8p4qbJdu3kfXuikYeDPbq\nair27SUsfWSn2e4I3G43Jz54D4exmqC0NAY8/DdBpHA7nWj79EE3eMh5HqWISMfRKgkuLS0NrdbX\nfXjXrl1MnDgRgIkTJ7Jr1y7Ak0hzwoQJSCQSUlNTMZlM6BuUptPr9ZjNZlJTU5FIJEyYMEE4vrl+\nJRIJdrsdm82GTCbjyJEjBAcHE91EmTsRERERkbOTv+47HMZqAlJSCBk6rNH+nw4Ucv+bv/LVtmwA\nwoPUzV5Eej0xSqosHD6jRwIMTQplYIKOYH8lJosnEXKgpmNEjPEDonjulhGEB3nCRryeGTaHJ0Sw\nvogROnyE8Lo1iT0DmvAebG2uBpnGMx6n2dyq9t0Nu8HAmf/7CoCkW/6Ef3w8LpuNqqNHhTY1hYVU\nHj7kU1K2PZTu+AWA8DFjSbnjTmF7+W+7zqlfEZGLlZr8fLbfdguZS1/m4PPPYTcYzveQWoXb7aZs\n1072/H0Bux99BEtZKW63m+wvPiNzyUtkvbuCY6+/istua1OfraVoy0+CgBE9ZSp9fn8Tff9yH/HX\nXgfAsddf5eCLL2DVV7T53DoDu7HaJyeTpayM3Y8+gn7fXmQaP1L+fKePl4VEJiN89BjkmqbDLEVE\nLkTa7RtVVVWFTqcDIDg4mKoqj6twRUUFYfUU1NDQUCoqKoS23jahoaGN2rTU77XXXstzzz2HTqdj\n3rx5LFmyhPnz57c4xk2bNrFp0yYAXnzxRWJiYppt29I+ke6PuH4XPuIadi3Wykp2bNgAQPpf/kpY\nbGyjNic3ngLgh30FAMRH6Zpdp+H9E/ji59NsPVgEQP+EUNJSegOw+N5gHnljM1UmK9HhwZ2y1v5+\nmYCRwKAQYmLCcTudHI6OQeGnIX5EOvnr1gKgi4holX37A/PZ89qrBCcmMeKB+ehaOWaVoYpMQGK3\nX5B/0+7cHJzmGsKHDGXgjKtxlxRzLCcHd2EBMVOnUXnyJL8+/SQumw1dal9Sr7uewl076TNlGhFD\nhwJQvHcPJ9asJn3+Q6iaCM0BMBYUYDh2DKlSyYDfzUDh70/I4pf5acHDlGzdQkhUFNqYWHpdOqEr\nT/+C50L8mxPxpb1r6HI4+PHfC322lW1Yz4h5LV8rn2+cNhsZL75A/vZtwjZ5WRlSi4X8td8J28p3\n/0b2u+/Qf+5N6E9k0XvKVOTNhA3qs7L4+cl/kHzNTNJuuhkAm9HIwXdXIFOrCU5MIm7iZciUSk6s\nWc3JD94DYNDtd9LvxjlCPw6LBWlNDbk//YTh2FHKN3zPiPkPgdvdbChGZ30Gz2zaSOmhgzitVnI2\n/0DaH29hwM23cGrtd+x+ZanQbsS8B0gYNKhTxnAxIX6Xdn86JMBLIpF0iotX/X4HDx7M4MGDAdiy\nZQvDhg2joKCAb775Bn9/f2677TZUDRK2TZ48mcmTJwvvCwoKmrQTExPT7L6OpqeHd5yPcBJx/S5c\ne166Yg17+ly21V7+9+twWi3oBg3GptM1Of+n8nyfOgWqm/4ejYmJIdzPgUYlw2z1PJ1PiwsQ2iqA\nR64fwKpfcxiZFNiutT7b+UlcHk+PgqISQtSeLOyDn3kWt8tN1fFjQjuj1doq+37D0xn/3n9xuVyY\nAXMrx1xjMgFgNlS16Ty7QyheTEwMebU5KjRJyRQWFiKJiATg1MYNnNqwAWt5XWk+/fFjZLzoCRfN\n+WETY1d4bgR+/fvfANgXFU3c1dcAvufndrs5+IInE37IsOGUVlVBVRXukFAhhOXge++CRMKo5a+h\n0Aa0+Vy6++evM+is79GePpfdYe28tHcNq0+dJGvF25iLCn22n/ruW5QJvQkfPYbS33ahCglF27t3\nB422ado6n4U/bCJ/+zZkajX+8QkYjh8jY1GdGBN/7fVYysoo+XkLhRk7KMzYAUDJqVPEzboW48kT\nAPj37oNMpaLox82c+uQjcLs5/N8P8B+eTuHmH6g+kUXl4UNCv4c/XYk2IYGSWvGkz+9vInD8pY3m\nP3buTegmXs7efzzK6fXryN22DXVEBAMeXiCED3rpjM+gVCql8ugRDr68GOrNaeZHH5L50Yc+bZNu\nvQ15337nNIaL+fPnpSPXsSvPr6esXWsFpHaLGEFBQej1enQ6HXq9nsDAQABCQkIoq1d/uLy8nJCQ\nEJ9jQ0JCKC8vb7JNc/16sVqt/PTTTzz++OMsWrSIhx9+mB07dvDzzz/7CBYiIiIiIo2pzDzMqY8/\nxFzoudiNmDCxyXYOp4viSt+QiMjg5l1R5TIpSdGBHMr2hA/2jvQNQYwL13L/NWnnMvQW8ebE8IaT\nAEIOh/oVSVpTneRc8F7UOi/QnBg1OTkA+MfHA6BNTALAWu93HaD//Ic8pXl3/Cpsc5hM1OTnC+9t\nzbhe2w0Gqk9kgURC7xvr8lpJpFJ0Q4ZQ8vNWzwa3G8PRo4R281h0EZHzTda7KzAXFaKOiiI4bQC2\nigq0fRLJ+forjr7xGkffeA0AqVLJyGWvdllYgdNqRX9gP9qE3qgjIhrtd9ntFGz4HoDk225HIpdj\nqCc6q8LCiJ1+FVKFgqjLL+fwv1/EWVvNKH/ddxT+sBGXzRNiEpCcgio0lLJakcPLzgf+6vM+Yvyl\nlO/eTU1eLjV5uQAk/vEWoic1fw/hFx1NUL/+VB09gsNYjdFYzZFXX2HAQw93eK6ghjhMJjKXvgwu\nF1KlEv+4OKpPnvRpEznxcmKmTMEvprFHpYhIT6XdIkZ6ejpbtmxh1qxZbNmyhZEjRwrb169fzyWX\nXEJWVhZ+fn4+oSQAOp0OjUbD8ePHSUlJYevWrUybNq3Ffr2sWbOG6dOnI5fLsdlsSCQSpFIpNlvr\n4+RERERELlYOL14kvA5MSW2UzNNLSaUFp8tNWKCK1F5B/JpZQkpsYJNtvcSG+gkiRnSIX4ttOxql\n3JsTo/ETAWl9EaMZ9+OOQqbxJva8MHNimGov6v17xQGg0umIGH8plpISYqZOw3TmDPZqA7pBg9EN\nGkzoiHSOvf4qAE5zDbbKuhxYNQX5WMrKUIWEQD3Xa+/TYm2fRM++eoSPHVcnYgBVx0QRQ0SkJWoK\nCzAXFCD392fYs88jra3g5na7MeXlUr5rp9DWZbNR9ONmel31u04fl9Ni4fDLiz2CJaCJjkY3eCi6\nIUPQ9u6D8fQpTn3yEZaSYjRR0YQMH4HLagWJREiumXD9bOF8AvokMvipZ6jJy6Vk+8/o9+/HZbPh\nHx+PpaSE6hNZVJ/IQqZWk3D9bBw1JnJWfY1EJsft8HjnKYN1JP3pNhKun83Bhc9jKSkm7ppZLQoY\nXqKvmEzV0SPCe8PRI2TM+yvauHjCx44jooNC39xOJ8YzZ/CPj0cql6M/dBCnxYJ/fAJDnnoaiUxG\nTWEBuatXYauoIG7mLIIHDOwQ2yIiFxKtEjGWLVtGZmYm1dXV3HPPPdx4443MmjWLpUuXsnnzZqEU\nKsCwYcPYs2cP8+bNQ6lUcu+99wr9LFiwgMWLFwNwxx138MYbb2Cz2Rg6dCjDhnmSyjXXL3hyaZw4\ncYLZs2cDMG3aNB577DH8/f1ZsGBBx8yIiIiISA/F0SDZZMy06UhksibbVho9FZtCA9XcMbUvN05I\nJPgs5VHr72+uFGtnoVTUVSc5fEZPucHKhEFRgK/3hbSTPTGkCgUSueei2WW3dfpTuo7EbjLhMBqR\nKhQo64kLKbfXJd2snyQVICx9JHkJvTGdycZRY8Zem8cKwHDsGLsXPEToiHTSauPy8777ljNffg6A\nJiqq0RiC+6eR9vACbBUVnHj/XYzZ2R15iiIiPY6C9esA0A0ZKtzwgycku8+cuYKI4fleclDw/Tqi\nr5jcaV5pTouF0p0Z5K9fS01+PnJtAG6nA3NhoVDqsyFJf7oNqVyOVC5n3LsfkPfNGuzGasJGjfZp\n5xcdjV90NCHDhlOWsQNNTAxBSckU/vQjJz54D4VWS9pDj6Dt3QeAXjOuQSKVYi0vo2T7NiIunYhU\nLkcZHMzgx5/EcPwYIQ2+05ojNH0kgx57HFVYOA6TkSOvLMNaXoYh6ziGrOMU/rAR9UOPQEjo2Ttr\ngNvlwlJaSukv2yneukUQg7W9+1BT6AlrCBs9Rvi99ouOoe899zbbn4jIxUCrRIzmEmg+9dRTjbZJ\nJBLuuOOOJtt7BQyApKQkXn755UZtAgICmuwXPGEojz32mPB+7NixjB07tsWxi4iIiIh4MBw76vNe\n20IZS73J492m0yqRSiVnFTAA4sL9hdfSTiyF1xTK2nASq93F4i8PApAaG0hUiJ+vJ0YrqpOcCxKJ\nBLmfH3aDAUdNDcqgC0fEqCnxlKFVhYa1Kc+VXKjIUoO9uq4agvemqfJIJm63G3t1tSBgAGiimq4u\nphs4SKiqYMrNwe1yNZtET0TkYqZi/z6Kt25BIpPRa8bVjfarQsMY/PhT4HahTU7hwLNPY8w+zd4n\n/8HQp59F7uffRK9nx+1y4XY6fUQTgMrMTI7/5w3h86uOiCDtwUdQhYVRfeIE+gP7qNi/H3NhAf5x\ncSgCgwhKSyOoXz+hD4lEQtw1M1u0L5XLibhkvPA++rLLCRk+HIlM7hMq4/3eUIWGEXfNLJ8+FIGB\nbfbyCkzt6+kvJIQRi1/GYTSiP3iA3NVfU5Ofz48PP0jvG+cSO/2qVvfptNnY+/jfG4XsARizTwMg\n99cSPnpMm8YqItLT6ZDEnhcK0hYuglra11VjEO11f7s9fT7P1/p1he2ePpetsVeVeVh4rRs0CE1o\n00+MDmVXsGKdJy5ZF6BuVd9SqZTBiWHcOb0fCRHaDj//s/WnrC2x6nDWhZNUWxzESKXI1XUXtQo/\nTavPp73INR4Rw2WxINW1rp/z+dnzYir2iBjq8PA2jcebB8RlsQg3Lym330nkpRP49Z47cdbU4DSZ\nfGPVJRKC+/Zr1o4qOBilTodNr8dWVtak10ZLdMfPX1fQGePo6XPZXdbOS2vH43a7BVEw4fob0MY2\nXQZaVysQuFwuEq69jsNLX8ZaWkrxli3E/W5Gq8dV/PNWyn7bhX+vXhRv24a92kDyrX8masJEnDYb\n2V98JuS38O8VR8zUaYSPGYtM6RFydWlp6NLSSJx7E26ns1kvwLbinS9VYNOVkDoTWVAQUeMvJXzU\naHK/XUPu6lWc+eoLAhITCe7fOAeU2+nEUlaGOiJCEIpN+fmCgBE+egxRl0/CLzoGU14uEpkMW3k5\nuoEDUQTrGvXXGVzsnz8vHTWurjy/i23teryI8dtvv7F7927uvvvu8z0UERERkfNK5WGPiDH4H08Q\n1Ldfk21MFjv//uKA8F6nbZsnwaUD23az2VF4RYz6OTGcLk9cdVeGkwDItVooBnt1NTTtbNDlmIuL\nqMnPJ3T4COxGI/nr16GJjiay3tNMU7GnPK4qLLxNfctqRQyH2Yzd4AknUQYGIpFI0ERHYzx9mtOf\nfYrxTDYAcTOuJnLi5WiaSPRXH218AhV6PcacM20WMUREehJul4vyvXswHD+O02rBaTbjdjqpyctD\nGRxM7NTpreonZOgw4mZcTe6331Ca8WurRYyqY0c5/s7bAFTs2ytsz3rvHUy5uZTu+EUQMAH6/3Ue\nmujmv/w6SsDoLsiUSnpfdwNym43T69aSuXwZo15aitzf19Ml6/13Kf55KzFXTiHxD39EIpEI4SLh\no8fQ7966JKTK4GCge1bvEBHpDvR4ESM9PZ309HSg5S+Arv5yEO2J9kR758dmT5/L5uxZ9XpqCvKR\nqlT490lstt13GTk+7/3V8ladw/leP4XM81SruqYuybPZ6vC0r/+0QCpt01jbc17K2mTWlvJyAtp4\nfGfN429/ewTwlCss/GGj54ZDKiUgJRV1WBgANSUlgMdVui3jkNV6uthN22xGaQAAIABJREFUJmy1\nOTFkAQG4XC6UuhA4fZqirT8BIPf3p9c1M5EqlGe14RcXT8X+fRjPZLc7uWd3+fz1BPs9fS7P99p5\naTgOa3k5mUtf8qn840UiV5B4y62t+l7z7u91zUwKftiE6cwZTn36P6ImTcZ4+hQF368nZMQIYq6c\nisNoRBEUhEQiofy3XZz86L9CPzI/PxJuuBH9gf3o9+2lYMN6zw6plOC0AaT8+XbUoWEX5foNv/8B\nyk5kUZ2VxZ4n/0HI0GFETJhIwbp1VGefwlLkEYoLNm6gYOMGYq/6nZBHSB0VLd6ndCM6ejxdeX4X\ny9r1eBFDRERE5GLGbjRiyDouuKsG9e2HVN70V3+l0cqGPb4XygEaRZNtuxvenBiGGruwrcbqEF6H\nDB2GvboaRUDLFVY6ZCy1br/1K3WcL/QHDwgVRwByvv6qbqfLRfGWn0i4/gYArLUX04rAts2RzM8j\nYjhMRiylpQCodJ7EoBHjL6Viz26hbdio0a1Oduot82rKyaH65ElKftlOwg2zu6w8pIhId8CbIFMZ\nEkJgcgpVx49hr6xErtXSf958AlNS29SfVKEkdEQ6Jdt+Jn/dWvLXrRX2VZ88QeHGjdj0FQQkJaMM\nCRESgwb160+/+x9AplZ7yiEPGMiBkyeQBwTSZ+7vCR44SKgYeLEilclIvPkWjixbirW8nMIfNlH4\nwyafNnJtAA5jNQD5a78TtrfkuSIiItIYUcQQERER6aE4bTb2P/0U1vK6hGHBgwY1237NjhxsDhcj\nkkOZlt6LrAIDg3p3TRzuuSKIGOY6EcNcT8To/8CDuN3uNiWsbPdYaj0xbPrzK2IYjh8jc8lLjbar\nwyPoc9MfOPLKUgq+X0fs9KuQ+/kJXhTygIA22ZHXlpWtyjyM02xGHREhuEKHDhvOuHfe5/h/3qR8\n316iLr+i1f36xycAHhHjwL+eAUARoCV+1nVtGp+ISHej6vgxslf+D01UNCl33NlseIXb5aJsp0dE\n6PfXeQTUJmO2VVUiVaraLejFXjUDS2kpbpeT6qwsn302fQXgETQ4CVKlkt43ziXq8kk+CXbVERGk\nv7wUiVzRJd+rFwra+ATSX1qC8fRpTrz/juBBkzB7DpGXTkAREIDDbMZckE/e2u+o2LsHv9heBKcN\nOM8jF+lJnCw0kFNi5LLB0T328ymKGCIiIiI9lOKtP/kIGEilhI9uvqLTruOetrPGJRAXriUltusT\npbUXVW1OjAqDRdhW3xMD6LIf8u4iYugPenKbaBOTMJ46KWwPSE4mIDkFAJfdzr6nn2TYcy9grc1n\nodC2TcSQ1d5IVZ/02Ajq73sxLpHJ6Hff/bjtdmjGC6gp1OHhSNVqH4+W+nH3IiL1sVZUUHUkk9D0\nkZ1WPrQjcNTUcPytN7HpKzBmn0Y3dKhP5QlbVRWKwEDsVVUcff1V7IYqVKFhQtlQAGVQ8DmNwS86\nmkF//wcABZs2cPqTjwkeMBC/2FiC0gYiVSo4/p83UYdHkPznO/BrxkvgQioh3ZVIpFICkpKIvnIK\nJz94H1VYGDFXXinMl1yjISApmf73P4DL4UAik/XYG02RrqfKZOO1NZnojTbUSjlj+7ecf+pCRRQx\nRERERHogLrud/LVrfbaFDB2Gopmn7FsPFlFttqNWyOgV1r6ye+eT3pGe8yqurCdiWJznZSyqbiJi\nVB05AkDcNbOwlpZw6pOPAI+IodBqCUhOofpEFtbSUnLXrMZa5REIFAHaNtnxhn1I5HICk1OImTq1\nURuJRIJEefY8GD7HSKX4x8X5PCmW1Xp9iIg05Pjbb2I4dozTKz9BFRZOyJChxM26ttvdHGZ/tlLw\ndgA49dF/kWs0GE6eYPua1XUNpVKo/bwEpqR22nlEX3ElftExaPv08Sm5OmrZq51i72Ii8tKJSOUK\nggcOalbwaS68U0SkPTicLl7/xiNgpMQEMjI17HwPqdO4qD45YonVnmevq+329PkUS6z2HHvFv/6C\nTV+BX69exF09k7JdO0m59c9Njiuv1Mh7G44DEBqkQtaOzPHne/1iw/wJDVRRbrAK28x2Z7vHdS7n\now7xlK61Veob9WMpLSXrvXeIu2amUIKvYt9elIGBBNZ6R5wrVcePU77nN487OBCUmkqloy7MJig5\nBalUysBHFqA/dIijry2nYOP3Hk8JQBkY1KbzD0pKZvQrryHTaJp9At7e+dTG9/YRMeRqVaeXyG0P\n3SUPwMVaYtVSWorhmKcstMNkwmEyYTqTjbWsjKSb/9ioSsS52msv+sOHKN66BYlczrB/Pkv2V19Q\nsW8vmUtfbtzY7RZeRowb16nfZSGDBrer7/ba60i6y2fPi894pFKiLp3Qcf11AT3dXmu5EEusSiQS\nPtyUxfF8A8H+Su6fOQClovNu9c/32vV4EUMssSoiInKx4XI4yF29CoC4q2cSMWYsEWOaDyP56UCh\n8LredfMFhUQiYXDvEH6sdy41FkcLRzRGb7RyssDAiJRze3LhDSex6vWN8nAUbPyeyszDOMw1DHv6\nOax6PYdrb2Am/Pfjc7Lr5eRH/8WUcwbwJOlU+PsjU9aJC/5xHs8JucaP8JGjKB87jtJff/HslEiQ\n+7Xd28GbA6Oj8Xp5eHHZbM20FLmYKdnh+fsNGzmKmCunUHn4MLlrv6Xkl22U/LqdfvfdT/jIUU0e\na8rPp3zvHtSRkYSNSO+U8bldLnJWf03Bxo0AxM+8Fv/4ePr/dR6nP1uJ4cQJzIUFOC0eT7KEG2YT\nNfFy5H5+1OTl+oSSiIiIiDQkt9TI4x/8BoBCLuX+mQMI1nbfsLqOoMeLGGKJVdGeaK/72+tKmz19\nLp0OB3sffwxrRTnqyEhC00e2OIaiiho27y8Q3s+d2Hz51ZboDus3sLfOR8QwWuxtGtfzK/dSUmnh\nrul9GT8w+qz2mkOiUCDz88NZUyPEtwO43W7K9+71jO30aarPZPvkeDDm5KDp1avN9upjq6wUBAzw\nJOVzuVxok5NRh0cQNGAAbokEd73zSrh+dp2I4XbjBp/9HUlb59OvV5zPe4fF0uklcs+F810m8GIs\nsep2uyn5xfP3Gz7uEgJSUj3/+vblxHvvYC0r4/jbb6GJjsZuMFC2MwNbVRUpd9yFuaiQQwufx1Xr\nhTT4iX8SkJTUcefgcGApLsZWqSdn1dcA+Cf0JmbqVM/5yWT0uelmob314AEqSkqIvmKysM0vPqFD\n5r67rt+Faq85OmscPX0+u8v6eWnteKx2J4ey9aQlBKNRNn9b3VnnV2awkFdmYu3Ouipkf5qcTFJ0\nQLe4LutMeryIISIiInIxYS0rw1zkuZFPuuU2n2zyDXG73Xy0+QQOp5tLB0Ry+7S+XTXMTqF/fDAy\nqQSny+NOYjA1/dR+1/FSivRmZoyK8/GSKKnNp7HvZIUgYrQXlU5HTU0N1kq9IGKYiwqxlBQLbYp/\n3oo6oi7hVuWRzHMWMfSHDvq89z7ZlWs0jPh340olAKrQUHrPvYnsT/9HQFLyOdnvaPwazIf3fERE\nvNTk5mIuyEeu1RI8sK76UnD/NNIXL2H/c09jPHWKvY8/5nNcxr2NPXSzv/ycgX/7+znnnzCeySZ/\n3VqqjmRiNxiEssuBffsycMHfm61G0mfqNFQFBU3uExER6V64XG6e+O9uSqssXD0mnusv6d11tt1u\n1u7M5ctt2T7bfzcqjnFpkV02jvNJ9wxEEhERERFpF5bSEsBzsRycltZi29+yyjh8phJ/tZzZEy58\nd2U/lZzkmEDhfVUTIkaN1cGKdcf4als2hRVmYbvDWfckwWI/94Sg3puW+sk9K2q9MLzhHKW//oIp\np+7pSe533+CoMZ2T3craiiRBtWuffNvtrTouduo0rnj1dfred/852e9oZEol4eMuEd6XbPsZU07O\neRyRSHejbPcuwBNK0lSSxN6z56KOiEQRFERAcgoSuULYJ/f3JzAllRGLFiPXajEcPULZzowm7VjL\ny3DZWw5nshuryf9+HQdffIGyjB2Cp5W3wk7MlVObFTBEREQuLIr0ZkqrPMJ6QXlNl9r+fne+IGCo\nFTKGJIZw5/R+zJmYhLSbJTPuLERPDBEREZEehLnEI2Kow1suqWW1O1n5o6ck5vXjexPo1zNK5Y3t\nH8GxPE+pUKPFgcPpQi6r0+szjpZgc3gEi+JKM5E6DaeLqn3yghTrz/1ipGGZVVtVJfnrvgMgbuYs\nclevwpSbQ1ltLD+AvaqKnNWrCB89hqpjR4mdOh2JVErV0aPI1KqzxsW7nU4qDx8CPF446vDwFj1x\nGhKS2hdLN3wKnHrn3YSNHMWRV5YCsO+fT3DJ+x+e51GJdBdqcj1CYFC//k3uD+rXjxGLFgvv3S4X\ned+uQdsnEd2gwUJyuoQbZnPyg/fJ/mwlusFDkP8/e+cdHld17e13qmY0qjPqvViWqyz3bmxsqgMY\n2yEBEi5J6AkhkPIFSC7kpgCBBFIgQLjABYcSbHqoNu7G3ZJsuahavc6MpNFo+pzvjzM60liSLdmy\nLcvnfR4/1pyy1z5nz5yy9lq/FSgdDGKE0+Gn/4TOFMPEX/wSXUyPbo4gCNjKymjc9BWtu3cj9BLR\nNaSlkXTZFTRt2YzLYiZyfP99lJGRufCobumU/u5v0uRsYXd6+OBrMW10SpaR26/MJUyvOe9Cm+ea\ni8qJIVcnGX32zrXd0X4+5eokF749VyASQx+fcNI+HKoyY+l0kxpj4NIpySiVZ+a5Hynjt2RKEnmZ\nJn6zZh/tXR46nV6M4Tpp/dZDPekc+8vMvPx5CTaHJ6iN1g4XoDijcxJiNALgaWtDoVBQ/uoreDs7\niZo4iZgZM3FbrVT863UpF3/iTx6g+C9P07D+Sxq++BwQq5yEZ2Vx6Ik/ALDwFMKfHRXleO12dHFx\nGBJPLx3mbI3jmbbb+4VyMO2N9t/7QFxM1Uk8djsN67/AcmA/AIak5MHtq1SSvmJlH3uJlyyhafMm\nOisrOfTEH5h43wO07ttD07at2KvEFwZnSzOlL71I3i8fwudw0LxzB40bN2KvCUQHKRRET84j8dKl\nGKfkS1EXCYsu6SPye6bHP1hG6vhdqPZOhTx+I9veYBlMv8obbNLf1k5Xv/sM5/H5BYGtBxt5b8dx\nnG4fE9Ki+OmqnspCF9vYjXonhlydREZG5mLC2SS+pPfWWjiRtk4Xf/ugGIA54+PO2IExklAoFMRE\n6ogKC6G9y0Ob3S05MWpaOqlo7Hno2HqoEYAog5YJaVG0d3korrLi8wu0291Eh5++sndItOjEcFkt\nmPftxVJwAFVoKGNvux2FQkHcvHlUvv0mgteLUhuCaeo0ki5dSv2G9VIbtoqKIA0Nr6MLtX7gyiHW\nIjGVJDpvymn3e6Si0umCPrusVkIC0S4yFyZ+txsUCpQazak3PgFBECh96UXM+/dJy3QJCWfUH4VS\nydjv307R47/HXlXF7gfuC1ofmpKK22ql49hRtn3vlqB1mvAI4hddQsLiJegHuPaeqc6GjIzM+cHj\n9bOnpIWthxqJDtOyakEmr3xRQlGlRdqmrdON3y+ctecpv1/g2Y+K2VPSCkBqrIFblg1PWfYLlVHv\nxJCrk8j2ZHsj3965tDnaz6W9thYAfWLSgLa3HOxJnZiabbqglO8HayfSIL4Ytdlc+OPEfbqPOyYi\nJBBtIbJ0ahLXzBZ1Kh55fT9VzZ20tjuINGhO+7g0gZKjLquVjrIyABKXXYYmKhq/348q1IBx6jTM\ne3ajT0hAANJWrqJh00YEn6jJYS0qxNnaKrXpaGnFcBLhz7Yjh8VjHz/htPt9tsfxdNtXaIPTndpL\nS4iZMfOs2TtdzrfC/oVSncTb1cWBXz2I22olesoUTNNnYpo2HbXBIG1jKT6ESqvtIzYrCAKVb/wr\nyIGhCQ9HoVafUR/9fj/6lBTG3Xsfh554DASByAkTiZu/AG1UNBFjx9J26KCU1gSiYyPlG9dgmj5D\n0uM40/MkV7e4MOwNhDx+F4a9U9G7P3/94BCFFT0Oi23F4uSCXqviurnp/Gd3DTaHh3XbKli1oP+0\nzzM9vk/31LCnpJXQEDXfuTRbnIBSKPpt92IZu1HvxJCRkZG5WPC5XKKwp1KJfoBZyU/31kpiUFfO\nSCHJNPDM/oVMmF50YnQ6e1JFjjeJ+auX5CWyrpeid0Roz0ywMTyEquZOzDYn2fSIhJ5IYYWFD76u\n4vJpyXQ4PLg9PjodXuZOiCM9LixI2FMbcGh0p5h0k7TsMiz79xE1cSIAmrBw1OHheNraAKQqM920\n7NiG4YZv99sfn8uFraIcFAoic8cNfGIuUFQhwZEYtrKyQTkxLmTcbW1YDx0kZuYsVCGnHxU0Emnc\n+JWkF2MtLMRaWMjxf79FdN4UYmfNJjwrm+I/Pg5A3PwFpF2/Em20EUvBARrWf0n7kcMo1Gpy7/4h\nHaUlROSMHba+ReaOI+/Xj6DWh/a5jhrzp5JyzbW07NhB/OLFJC69rE+qk4yMzOih3txFYYUFnUZF\nfraRnUdbAIiL0vHQt/OJMmg5eNxCcVUbH+2qITclkkkZxgHb8/r82Lo8fSI9BUHA4fYRGtL31bzO\nbOeDnWLK2h1X55KfZRrGI7xwOW0nRn19PU8/3eONbm5u5oYbbsBut7NhwwYiAiXlbrzxRqZNm9Zn\n/4KCAl555RX8fj9Lly5lxYoVUjvPPPMMNpuNrKws7r33XtRqNZ9++inr168nJiaGn//856jVao4e\nPcrOnTu59dZbT/cwZGRkZEYNXfV1IAjoExP7DdH2+wXe3lwhfZ477uTinxcy3Q8CXa6eSiNdLi8A\nKTGGoG17i5oaAw8WFpuLk7F2WyU1LXae/+Ro0PIGaxf3Xz+pl7CnBW9ABFATFh5sd2wuM/78FzS9\nZp9VGi29FToicsaiiYrCvGc3dZ9+QvwlS9DHB5dPEwSB8tdeRfB6CcvKCprNHi2c+BJvKy87Tz05\nN3gdDop+9z+4zK207vyaCff/dFRVtegWoNUnJmKaOYu2gwfprKygZcd2WnfvImP1DdK2zdu30bp3\nD35Xr9+kUknu3T/ENG06pmnTh71/4ZlZA65LX7ma9JWrh92mjIzMyKK5zcFDr+4FYFZuLN9ZOkZy\nYiyfmUqUQXx2uOcbE3j1yxL2lLTy1LpDzB0fx9L8pKBqaSDeq5/96AgHys3cvCSbpflJUvrJhoJ6\n1nxVztL8JBZOiud4UyczcmKwO708+c5BnG4fM3JiZAdGL07biZGUlMSTT4pqz36/nzvvvJNZs2ax\nceNGli9fzrXXXjvgvn6/n//93//lV7/6FSaTiQcffJAZM2aQkpLCmjVrWL58OfPnz+fFF1/kq6++\n4vLLL2fbtm08+eSTvPfeexQUFDB9+nTWrVvHfffdN6AdGRkZmYuJhoCeQnh2/3mSR2vbgj6P1igM\n6OXEcHqlZY6AEyMhOnjmNLJXJIYp4MQwdwzsxPALAk1WR9CyvEwjRZUWSSRUEx6OQqXCa7fjCsw4\nq8PD+7SljTgh2qNXJZXkq79B8lVXU/P+u9KyzsqKPk6Mmg8/oGXHdpQhIWR/99YB+30hozYYSFu5\nGoVSQdXad7CVleJub0cbGXm+u3bG+L1e6j//jJCYGGJmzUahUNBWfAiXWUwlais+RNW6tWTc8K3z\n3NPhwxmoojT+x/ejT0gg9RvXcPS5Z7EWHEDweql8642g7bsdGEqtlrQVKzFOnTZgtJmMjIzMUBhI\ndLf3JMXl05PRqpX8+qZ8jtW2s3BSz/XHoFNz9/LxdDkPUlzdxtdHmimusvLMXXOobrLxyhclXDcn\nDY/Pz4FyMwD/2lhOS7uTm5Zkc7jaypqvxGpxGwrq2VAgVgkrrrJS0WCjze5mfGokd1yVezZPwwXH\nsMiKHjx4kISEBGJjYwe1fVlZGQkJCcTHx6NWq5k3bx579uxBEASKi4uZM2cOAIsXL2bPHrH+tyAI\n+Hw+XC4XarWarVu3kp+fT1hY2HAcgoyMjMwFTVd9PU3btqJQqUhZ/o1+t+meQTBFhPCjayegUY9M\nVfDhQB9wYjjcPU6M7qiMcL2GcH2P4yLC0F8khnPAtuvNXVKZ1m6+tUjMg3UGbCiUSkmM0tUqnnfN\nIO5Xyl6z7RnfvAFNWBjJV10tLbMc2E/tJ/+RtDKad2wXnRwKBbl33UNYRsYpbVyopF5zLSnLr0Ed\niGjZ85N7OfDrh/Ha7ee5ZwPjMps5+tzf6Sgr7Xe9t8vO4T89SdXaf1Py/HO07vwaZ2sLx579GwCR\nEyaAUkndp/9h+/duwVZefi67f1bwezy4LGZQKAgJRCkpNVom3Hc/Y++6B4VaTUhMDKYZM8m54y7m\nvvgS4+69j4icseT84HaSr7padmDIyMgMC/tKW7ntmW38+rV9/HtLJVXNnQiCwFcF9VQEqo9cPy9d\niuDMTozg6pmpfQQ8lUoFdy4fx9L8JAA6ujy8v6OKx98uoLLRxjPvF/PKF8H3gS/212HtdPHy5yXS\nshlje8o37ylpxWxzMSYxgvtWTEKrGT3ReMPBsGhibN++nfnz50ufP//8c7Zs2UJWVha33HJLH0eD\nxWLBZOoJhzGZTJSWlmKz2QgNDUUVeIgzGo1YLKKQypVXXsnDDz9MSkoKubm5/PGPf+Thhx8eju7L\nyMjIXPBUvbsWBIG4hYv6zNSDqK69r1R88X1g5SSSTaMv5aA3oSHifaS5zckjr+9ncka0FImhD1ET\nrtdIURMR+mBNDADzSdJJSuvaxf1CNXR0ebhmTho6rWivt9NEGRICdrv0kn1iOkl/KJR9H1JCTDHk\n3v1Djv3jWVp376J19y66amuIv2QxZS+/BEDWTd/BmD/1lO2PBkwzZtC0aSMAXbU1NG/fRtzCRTjq\n6/qIQJ5vSl56kY6jRzDv2c3s514I0k9wmVsp/vNTOOrrpWXNX++gYcOX0ueU5dcQPXkKx99+U1y/\nfSvh2dkD2nN3dIDfL+mwjBSad2zHVlaK1mjEmD8NBIGQmBhJDLOb2NlziJszF8UJgnVnK21ERkbm\n4sXr8/PO1kp8foGaFjs1LXY+2VMDr++Xtlk5P4Nr56QNqr2IUC3fXToGn19gU1EDHwZ0LLrpcnlJ\niNbT0eWR0lvf21ElCY0/9K0pjE2JpNPh4UfPfQ2IVUjuXzlJesaQ6eGMnRher5d9+/Zx0003AXD5\n5ZezerWYK/j222/z2muvcc8995ypGRYtWsSiRYsAWLt2LVdddRUFBQVs3rwZk8nELbfc0qde7fr1\n61m/Xgyvfvzxx0lKShqw/ZOtkxn5yON34SOP4enTUV1F657dKLVaZt5+J/qYHk/+y58UcqCkiYzE\nSOxOL1mJUcycPPxluUba+KW0+oBSKXSzqlkU9dSHqElNSabeslXaNiM9VfpbpYsECmmze0gYYLa3\nbrP4YPKdyyezMC+VqLAQnG4vsBuXxy+dixBDGG5Lj6J5ak5OUKRFf2j1OrrjCnqfU+PixVS+sQbB\n58fTacOyfz9tBw8i+HzkrFhJ/i3/NZjTckpG2jj2h/Gue/go4MQAiDaZaP3kY8o//ohpP/ox2dcM\nnM56LumorqLj6BHpc9mzf+XSP/8FgK7mJrb85Rkc9fVEpGcw84GfseG+H9F2sEjaPmXhIsYtuRSF\nUomvqZGaTRtx19f3O0aCz8fuJ5+gar3oAFnyp6eJmTT5LB/h4LCWllL6zxekz9Xr1gIQlZZ+QXzf\nzjXyObmwkcfvwuHv7+6j0eog0WTgx6tmsqWoms93VeIXBML0Gu5dOYMl09KH3O5t10ZS3boVS4eD\nG5aMx+Zw8+Z6sXrY/7t5Pimx4Xy5r5IXPyxgy0Gx1PvCvFQWzxovtTE29RglNRZ+ftM8ctJkHYz+\nOGMnxoEDB8jMzCQq4PWP6uX9X7p0KU888USffYxGI2azWfpsNpsxGo2Eh4fT1dWFz+dDpVJhsVgw\nnqDmbrFYKCsrY/Xq1TzyyCM88sgjrFu3jkOHDpGXlxe07bJly1i2bJn0ub7XbEdvkpKSBlw33HQ7\nWs5VOZrRbg/k8buQ7XVzLsbwdI9NEAQ6KysJTUlBdUKZx7Nh72Q4mpvwO10Y0oJnBSre+TcAcfPm\nY3W7sQbO5bHadt7aIL5EHasRX6Zn5kQP+7keiePntHf0u1ynUVJfX8+ccbHsPNrCFdOTg/ru9flR\nKMDa4aS2rp7uiFGXx8fbmyuYPS6WojLxoSMuTMBlt9JkF0VTQdTdqK2rE0uf9dK3UBsMNDY1nfL4\noqbPwFpSQuSEiX3O6Yyn/4rXbmf3vffgcznxuZxE508l9pprh+X8n81xHO7fQ8zsObTu2glAa0M9\n1R9/BMD+v/8V/fQZI+LaeeylfwZtYy4u5ujmzUTk5FD4m0forKlGExHBuJ/9AmdYGBFjc+koOQbA\n+Pvux5g/VfrOJH3zBmo2bcRaXk5tVRVKjQZ3Rwfq0FAUKhUVr/8fjRu/kmxV7NiB2zg8D75nei6L\n//EsIIrUdpSKYdOhySnEXn5Fv9+3kTB254uz8Rsc7edTHr/hZTTbK6gwo1QoJA2rD7eXolYpuP2K\nHBLD/XxrfgrXzkhAERKBz9mOQac57fH89bcnIwBqlYomaxfvqBRkxocTpXVh73AzNS2UvEwjbq+P\nmAgdV02LD7J199U52Lo8RKhdg+7DaBm7wToCz9iJcWIqidVqJTqgyr57925SU1P77JOdnU1DQwPN\nzc0YjUZ27NjBj3/8YxQKBRMnTmTnzp3Mnz+fTZs2MWPGjKB93377bW64QVStdrvdACgUClyukyvJ\ny8jIyJwO9V98xvG3xFDulG9cS/qq86NK31Z8iCN/fQaAmU//FXVojyhn2yFR6T9u/kJpmSAIvLv9\neFAbpvAQKV9ztNNfmbLey29aks20MTFB+acAapWSKIMWa6ebP687iDE8hO9fMZaNhQ18FfgHEKJR\nkhrbkyqpVCoI0Shxefy4PD70WnVQWVB16ODSdxKXXY4+MYnwMX3ZNicZAAAgAElEQVSjZRQKRZCu\nhkqvJ/fOu1EoR6+2yUCkr/6m5MTw2GxowsPx2MT8ZcHng/N8ThzNTbTu3oVCpWL6E09S+Lv/wdPW\nxsE//JaoyXl0Hq8EYML9P5XGNONbN3LoiT8QO3den9QgdaiB0OQUuupq+fqOH0jHG5qcTFhWNs1b\nt6DUaDBNn0nLzh04mhrPqP+dx49jLSokJDaWiOxsQhMST6udtsPFtBUfQqXXM+7H92GvqUGp1hA+\nZky/QnoyMjIyw4XfL3Cg3EyXy0toiJq/f3gYAUiPC6O1Q9S9Wjkvg6zEHoFtfYiapKQo6uu7zsi2\nQqGg+woXHx3KY9+bSZhOLV339CFqHlg5acD9o8NCiA4bXaW1h5szcmI4nU6Kioq44447pGVr1qzh\n+PHjKBQKYmNjpXUWi4UXXniBBx98EJVKxfe//31+//vf4/f7WbJkieTsuPnmm3nmmWd46623yMzM\n5NJLL5XarqwUb/pZWWLpqwULFvCzn/0Mk8nEdddddyaHIiMjI9MHwe+n/ovPpc+tu3eecyeG4PfT\ntHULFWteR/CKGg6OhgYpL97vceNobACFIkjU8Uh1G8dq2zHo1Nx59TiO1bZz2dSki0YY6lROjIhQ\nLbNy+xejNoaHYO10c6hKrCry7cVZWDuDHeVZiRGoThD20mvVuDxunK5uJ0bPA4gqdHCVYBRKJdGT\n8066TWhqKl01NaSv/qYkHnqxoYuJJef2Oyn95wt42tvx9ZrIcLe346irRRAEovOmnJf+WQsKQBAw\nzZhJiCmGiDE5mPeKQuXdKSPa6GjCMjKlfcKzspj993+gUPf/3c288SaK//wU+P2Sw6arro6uujpQ\nKJj9/x6kw+U+IydG847tVLz+f/icwcK2iZcuJePGm/toWAyE4Pfjc7moCkSJJV+9HE1YOFHjJ5xW\nv2RkZGSGgt3p5bmPDlNc3dZnXXd6qSk8hEvP0cRObOTFea8+m5yRE0On0/Hyyy8HLbv33nv73dZo\nNPLggw9Kn6dNm8a0adP6bBcfH89jjz3WbxuZmZncfffd0ufly5ezfPny0+m6jIyMzCmxFBbgtlgI\nMZlwmc04W1rwud1SWonP7cbZ2NgnvWM4Me/dQ/mr4nVWqdPhdzpxNIpOjK76OspeeRn8fvSJSai0\nWims76PdNQBcOSOFvEwjeZnGAW2MRvQhPc6anKQISus7AstPfdszhodQHlAlB7DYXAhC8DbZiX1F\nOnVaFdhhzVdl3HvdRFHYM4B6kE6MwTDuhz+m83glMbNmD1ub55OKRhtdTg+TMob2HdUEStY6m5rw\nByIzAQ78+iF8XV0oVCpmP/t8kDNpOBH8fiz79+Hp7CRu7rwg0c62w8UARAd0KdK/eQPaqCjiFiyk\n8NH/BsDncPRpU6nR9FnWTdTEScx46mlAwLxvL46GBrx2O46GehIvu4KUhYuoPHgQAEdDI4LfP+Qo\nHcuB/ZIDQ5+QiD4pCWtRIQ1fbUAVFkb69asG1U7lG2ukks+ayEiSLrtiSP2QkZGROR0sNhd7SlpY\nf6CelnYnYTo1ualRWDqceHx+br50DArEiYzYSN2ortI22hmW6iQXCicKfw523bnqg2xv5Nsd7efz\nfI3fubB9Ou03BXLMky67gsbNm3A01ONqaiIsXRR6OvTMn2k/cpgpv/pvInLGSvs1f72D4++8Tery\na0hcuqzftgdLV10tAJHjxhMxdiw1H35A6UsvEp6ZyZG/PI2zuRmA8IwM6Ridbi8lte0oFLBsavI5\nGdeRNn4RoSEkGvWEaFTkjzFJTgyDTn3KtkwRwTMm1k431k530LKM+PA+7bQFttlXZsYvgPoEJ8Zw\n3YMMiYkYEk8vvP9UnK1xHKjdvSUt/O3DYgQBbliUxTdmD94hGBIZCYC9tiZoua9LDAMWfD78Dgea\nXs6FoSD4/XQer6T6/fdIu34V4Zk9URP22hpKX35JKnnqbGpkzM3fBcDrcNB+RBRxi56ch1KpxJCQ\nyJjviuKrhvR07FVVhCanDPl86wOV3VIuv7Lf9TqTiRCjCZfFTFtR4ZArergCemVZN32HpMuvQKFQ\n0H7kCEWP/566/3xM7MxZhKUFC90JgkDJP19A8PvJ+d4PcDQ20NBLn2PMd/9rSGNwMd33+mO4+zPa\nz6c8fsPLubbX2uFi55EmZufGEht1etdqa6eLPcda2HWsmdK6Hj2stLgwfrJiEjGnEQUxXOfhXJ7P\n0f5dOZFR78TYu3cv+/bt48477zzfXZGRkbmAcDQ1YT1YhFKjIX7hQjrKSnE01GOrKCcsPZ2u+jrp\nRcV68CAROWMRBIGu2lrxgd7no+y1V4maOAn9AFUu+kMQhKBc8W4nRfzChUHlN/c/3BPZFp03hfTr\nVwLg8/u54y/bAMhKDMegG3hmdzSjVCp47Huz8PkFthxskJYPlGbSm+4yq92YO5yYbcHh9b31MLpx\nenzS3+12N8ogTYzhi8Q4F1Q12Vi7rZLU2DDmT4w/KyV5BUHgvR3HpSiXf2+pICJUw6LJg3PQhMTE\nolCpELzevuuMRlwWCz5n32iHwVL+r9dpCFT7cLQ0M+OxP4r99vspfvrPuFpbpG3big9Jfzdt3YLf\n7SZi7FhCAhphvZn4k59Ste4dUq8Z/jRYhVJJ8lVXUfGvNdR89CEdpaXUff4pmvBwdDGx+NxuJt7/\nACEDiH66WsUyzDEzZ0nXoeiJE0m67HLqv/yCkpdeZPIvHuT42n/j93hQh4Ziq6jAVlYKgN/tFq+L\nfj/GqdMYd9c9F23Kk4yMTDCFFWbe2VpJbkokGfFhlNR1sPNIMy6Pj493VfOT6yeh16r4fF8tVc2d\n5GUaabI6KKq04Pb6ycs0kpMcwbKpyRh0GoqrrLy/4zglte10B0tq1Erys4zMHhfH9JwYVCPMySUz\nfIx6J8aMGTMkcdCTqaeea1Vj2Z5sT7Z3fmwO1k79V2IodMys2ahCDURPyce8dw8NG9YTt3ARbUeP\nStu62qx4uro49OTjdFZUBLXT9PUO0q5bcUp7giBQ/NQT2CoqiMzNJWriZKImTsTRLFYnCImJxZCW\njkqv7wlDVyqZ8utHCQtEYfj9fhotPWJUM3JiRtx5Pdd2VEpRhLMbvVZ1yjaiw4Kr0Lz6ZWmfbWIj\nQk7ajrnDibpXNRulXj+ovp9vhX2/309rh5Mn1xbR0eWhsMLC/rJWfv9f04dFiLH38ZXWtVPTYidc\nr0GnVdHS7uSlz46RlxlNROipKwGpQkOZ8t+/wVZZgddux7J/H7byMgC0UdG4LBY89q7TOqfutjbJ\ngQEgeH1SO+3HjuJqbUEbHU3+o79lz0/vx15Tg6ujnda9e6l4Yw0ACYsv7de2JiqKMT+4vc/5GA78\nfj9xCy+h5sMPsFWUY6sol47H3Sbmhh978QVSvnENLV/voLPqONm33ErEmBx8LhceWwcKlQp1RERQ\n3zJW34B5/37sVVXs/NHd9MmvCmDetxeA6Cn55Nx+J4peKW6ncyznkvP92+vmbPVjtJ9PefxGtr2K\nRht/+6AYt9dPdUCTojddLi9/eKsgaFlNiz3oc1GlhaJKC+/vqMKgU9PRJeqEqVVixZFZY2OZkm1E\nr+15vR0p159zOX4X+ndlsIx6J4aMjIzMUPG53TRv3QJAwqVLAYidPZvqdWux11RT+/FHeO09N2FH\nQwO1n3wsOTBCk1NIX7mKI3/7C607vyb12utO+QLYVVtD++FAZEdhIdbCwqD1IbFxqHQ6Zjz1NHt/\n/gC+ri7Srrs+SMwToNEiOjhiIkK4ckbK6Z+EUUTvB5rBRGJkJfTVuwgNUbNwUjxpcWGBlJS+43nP\nN8bz3MdiSVtrp4sEXa90ktNMaTjXuDw+nn73kPRwCFBv7qK62U56fN/oE0EQcHv9hJyGYOyGArFs\n3CWTE5iSZeT3b4nf+V1HW7hsWvKg2jCkpUmaNLFz5lL+6sukXHsdNe+/B3DakRjdeg7d6APpOz6X\ni6N/+wsAxqnT0EREEJaZga20FPPevVT863UQBFKvu57YufNOy/aZogoJIenyK6la9w4gaoeEZWYR\nMW4c1evW0n7ksBRFBlD81B8JS8/AGYgsCTGZ+mhpqHQ6xnzv+xQ/9ccgB4Zpxkz0iYm4rVZavt6B\n4PMRnpND7j0/GlJJahkZmdFLm93NM+8dwu31ExupI8kUypHqNpZMSWRxXhIRBi2vry+hvMGGXxCI\ni9QRF6XH7fWTkxSBy+PD7vISH6Vn55Fmiqvb6OjySCmzK+elD0rvSmZ0IY+4jIyMzAmY9+7Ba7dj\nSM8gLFOshqTUaMm57XaKn/oj1e+tC9re0VAvVZ+ImpxHzg9uJyQiAk14BI7GBuxVVX2cDb3x2GxU\nBsq4mmbOwpg3hbbiYtoOH8LT0YHWaEQbyP9Xh4Yy9XeP4XM6CE3sq6rdYBUjMfKzTSjlEoZAQHAz\nQKju1Lc9U4SO33x3OoerrMRH6zDoNGQnhqNWnTwsdVZuLMdq29lQUI/F5iLpLAl7nk0Kys3UmbtI\niNbz65umsnZbJRsLG9hf3goKQIB12yvx+QSWTk2iyerg31sruecb45k5tv9qL/3R1uliT0krCmDx\nlERiInSSE2jroUaSY0KJNGiHlMYSYjQy4YGfAWL5WRD1KYaCu70N68GD1H78IQBxCxbSvG0r/kD1\nE2dLC167ODuYeq0YYWVITcNWWkrpK/8LiL/htBXXD8nucJOwdBltRw6jNhgYc+v3pBK/SpWKyjff\nAKWSpGWXUf/F5/hdLjpKjkn7mqbP7LfNqImTiL9kCU2bNwKQfNXVpF2/EqVGdFZETphIW1ERmTd/\nR3ZgyMiMMgRBYGNRA5GhWqaNMQ0pMm/3sRY6ujyMTY7gF9/MQ61S4hcElAqFpKtw1/Lxg2pr4aQE\nmqwOlEoFkaGai6bimkxfZCeGjIyMzAl057fHzV8QdKOOmjiJ5Kuupu7TT4K299hsdNVUA5B2/Uq0\nkZEolEpi58yh/ssvaNqyibCMW/utFuBobuLQY3/A3WZFbTCQeu0KDCkpxC1YiOD342ioRx0WHrSf\nmGffN9ceeiIxEqIvjJfmc0FvJ4ZeO7gHnsyEcDITwoccJtmdimK1uVFpe5VY1V8Y41FnFp1gM8bG\nYNCpycs0srGwgY92VvPB19VB2/YuXffsR0d4+f4YlEoFta12dhxuYsXc9H4fMAVB4B//OYrPL5Cf\nZSQmIKSan2VEH6KiusXOH985iE6j4qnbZxGmH7quizqgw9BfBZCTUfLi81JEVFhWFglLLqV521a8\ngYgOb6dYtSZibK7kWAxNSZX2V+p0ZN5405D7O9yo9Xom/fz/9VmedPmVhGVlo1CqCM/KIvXaFVgP\nHURtMKCLi0MbGXXSai7Z372FhMWL0Sck9tG6iJs7j7jzFH0iIyNz5lhsLnYfa2HBxASqW2yYwnXE\nR4sO4YPHrby2XkzXu/3KXOZPjD9le60dTtZsKKOgwgLAvAnx0mTAmUyydPdJ5uJGdmLIyMjI9MLT\n2UnbwSKAfkunpq1cjUKpov7Lz4maNBlXSwv2mmpJ1b+3YF7C4iXUf/kFzdu3oY02UvvRB4z78U+k\nsosA9Z99irvNSlhWNuPu+SEhphhpnUKpJDR5aCkhpfXtAKTHDb8Q44XKUCMxzoRIg+jE6HC4UUZd\neMKe9QEnRpJJ7O/41Ci0aiVub7AzxxQegsfnD0o7sTu9GPRqfvV/+wDxXFwxve/312Jzcay2HZVS\nwc2XZkvLtRoVU7NN7Dgsitk6PT6+PtI86NSS3nRHYgzFieHp7KT9yBFp//RVN0jOp+52PDbRiaEO\n60mtCet1nUhbsZKQ6JFdzjhiTI70t9pgIHb2nEHvq1CpCMvIPPWGMjIyFxRen58/rTtInbmLtzaL\nqbFhOjUP35jP9sNNbDnYKG372b5aEox6Pt9XR12rncV5idJ1WhAECissbDvcxIEyMz5/T/pZdmLE\nuT0omVHNReXEkEusjj5759ruaD+fF3OJVa/dzvF319K0ZTN+t1gq09BPCUSlVkvmDd8i84ZvAXD0\nH89iD0RhKDQaQgJRGEqlkvC0dEzTpmPev4/qd9cCcPhPT7Lg1ddRKBR47XZadu0EYOz3b0MfG3dG\nx2exuWiwONBpVGQnRY6q0l5n0n5orwotYTrtoNo6XXsRASdGp8NL9NwJhMTE4DKbMSSfvNTt+S5V\n1k19QBg2JSYMpVJJqE7Jz7+Zh7XTTU5SBPe/IH5ff3jtBNLiwmhtF0VAzR0uutw+Gtt6nAZ15i7p\nuLr/f3tzOf/ZLZZEHZcaRXx0sLPtsqkpfH24WVKaP3jcyhUzUhkq3U4jv8s56HPbcewoCAKREyaQ\n9/8eAsBltQLgc4rteDtFLRxtRITUbkT2GNKvX4UuLpbYufOHRQD1dDkb36PRfh8aKb+9buQSnSPb\n3qm4kMbP6/Oz5WAjY5Ii6HR6pEi8bjqdXh58Za/0OTXGQIO1i5oWO799o0eE818by0mOMRCm1/BU\nQBQaQKmAaWNM1Jm7iNBrSI0N66MnNdLGrxu5xOrIs3cio96JIZdYlZGR6Q9BELAc2M/xte9IM5ON\ngVzvbjThfQUeT0TfS5ciJDq6T7pIxre+jaWwAMHXU36zq64WQ0oqVe+/i6+ri8hx4zGkDv1F7UR2\nHBZnSsanRZ1Sv+FiIiidJOTs5s+GB1IfOh0eQoxGZjzxFF67XUo9GMl4vD6arA4UQKKxJ3IkNyVK\n+vua2Wk0tTnITAhHpVSSZDIQrteITgynl9b2nlK0RRUW/vDWAWblxnH59FTMHU7JgQGQHtdXKDQ7\nKYJHvzsdAYFHX99PRWNHn7LDg0F9GpoYzkbx9xOWntGnHZ9DPK7uSIze1waFUknGylXAyKmQICMj\nc/HicHvpdHiIjRw47cLvF3hjYxnrD9Sj1SjJSRLvUdNzYli9MAsQ+N0bB7A7vYxPi2Ll/AzGJkey\n61gLz310GL1WxaX5STRaHOwra+XTPTUcq2vH7RGvgZdNS2b5rLQ+JctlZIaLUe/EkEusyvZkeyPf\n3rm02W2n/PXXaAyUUXW2NKONFjUmcm67g+r31hE1OQ9BEBAGKCXYjT4hQfo7JCa2z3Ho4uJJWLqM\nhi8+l5aZ9+8HtZr69V+CQkHmjTef8fF7vH4+2yO+IC6ZkjhqvzOnY0ej6nkBDtEoh9TGUO0ZAgrp\nNodH3FepRB0+eG2N8/kSXNfaic8vEBupQ6NS9NuXVQsypL+71xt03cfsxtzR48Ros7tps7upa+1i\naX4Smwrrg9oamxLRr430OAOCIBCu12BzeGhu6zrpw3h/KAN6Dd4uR5ANT0cHLoulX6Fdp7kVAK3R\n2LOPRgMKBX63i67mJjy2DkBMJ+mv7+fbiXE27Y/Wa8r5sjcQconOC8PeQJzv8TtW28Zf3j9Ml8sL\niPpO8yfEExel42ClhZhI8dr45qaecvBuj5/iKjHqbEZODMmmUPx+P7/57jQsHS5ykiNQKBQIgsCs\nsTGkfW8GkWFa9Fo1B8rN7Ctr5eBxcf9kUyhXz0pl/oT4IfV7pIxfN3KJ1ZFrr5tR78SQkZGRORGf\n203jxg2gVKJQqvC73TibmlCoNcTMnkPsvJ6Q8HpzF29vqcDu9LI4L4EFE3ucFh1dbo56xRxPBWBI\n6V+/Iu3aFTgbGvA6HdhKS+koOYbaYAC/H9PMWf1qbwyVHYebaLO7SY01MDmjf9HPi5XeAmIG3dBF\nIodCtwilzeE5xZYjj+omUU+lWw9jsBhCxGPucnpps4upWGmxBqZkm/iqoB6bw8OGgnq2HGoA4CfX\nTyQmQkfySewoFAoyE8IoqrRS2dg5ZCeGSidu77aYg5Yfe/452o8cJuu7/0Xs3HlBpW/707VRKBRS\nSdEDD/2S6PypAKjDTh2lJSMjI3MuqWnp5Jn3inG4eyI/KxttVDbaBtxn0aQElEoFm4oa0GlVTEjv\neX6IidBJwsu9SegVqZfRK6JufFoUP105SY4ElTknyE4MGRmZiw5nczMIArr4eFRaLfZqUdPCkJaK\nUt1zWfT5BV789CjHm8Q8eIfLG+TEePjVfdgcHq4MSyG1s1ZKLREEgeY2B7GBGQ+1wcCEB36Go7GR\n/Q/+AnttLZooMUQ/ImfsGR+PXxD4ZI94DFfNTDmvOfkjlb/cNQevz49WfXYfrkJDVKiUCpxuHx6v\nH81ZtjecVDeJUQZJxqE5MbrFUu0uL9ZO0YmxfFYqs8fFUVLbzrHadl5bXwpAbKSOvEzjoJTpM+PD\nKaq0UtFoY1bu4Mu3AkSOzUWhVmM9WMShPz5O9q3fo2nTRtqPiJVHKl7/PyrWvIYhJZXwMWMIH5OD\nI5BOEmIy9dum3+PBvGc3AJoIWaBORkZm5NDp8PCndYdwuH2MT42kuc1JXJSOS/ISef4/R6XtFk1K\nwOH24vUJTEyPZtGkeDRqJUvyEomJ1BEeOrTyyFFhWvIyjXQ5vfzomvGyA0PmnCE7MWRkZC46nI3i\njLA+PgGFSiU5MfTxCUHbrT9QJzkwABqtDnx+AZVSQU2LXZptbwqNE50YCQm4vX5e/PQoe0taufWy\nHBbnJUr76+LiUGq1uK0WzHv3ABCelTWoPls7Xfzrq3I8Pj/3rZgY9BL49ZFmGiwOTBEhzBo7tJe9\ni4XuqiFnG4VCQZheQ7vdTafDQ/QIzQc+3mSjtK6DeRPipXSQ1nZRP6I73HiwdO9vd3pp63QBEB0m\nHve88XEcq22Xtl04KWHQpfUyE8Roh5PNIg5EiMmEMX8q5r17aD9ymGPP/h17dZW0PiwrC3tVFfaa\nauw11TRu/Cpo31Mx1KpBMjIyMmcLv1/g9Q1ltNndZCeGc//KyWjVSklPyOvz89JnJVw/L53r5qb3\n20Z6fF+NosGgUCh4YOWkM+m+jMxpcVE5MUaCMvxoV46Vq5PI9kaq7d7tO5ubAAhNCHZa6GJjpe1a\nO5y8u/04APevnMRr60sxd7ho7XCRaAwNcm7ops8lyziBjpg0/vZOEWX14oz2J3tqWDIlqScyIlAy\ntbOyAp/DQdSkyURkZfcRA+2NIAhsPdTIm5vKsTu9gb65SIjumS3fWCg6ZVbOz0SrOT+X9ZFcneRc\n2wsPODFsTi+mQaZBnO3j21zUwKEqCwsmJrBuW6X0/W2zu/nWJWKZ03a76ICINAyugks3YYEUnXpL\nl6RuHxOlR6lUsiQ/mfmTEthT0sq+0laWTT15lZbeZAeE5qqaOgFFH1X7gfjZ5p9R2FqIW2fFndft\nQNkFAX3SWWMu4S/X/Q8+t5vOygo6ykrpKCnBVl5OWEY62vCIoGim/Ed+Q+fx45T93yvSMv0Jjo7z\nrdLejVydZOTbOxVn2h+LzYlfgBCNinC9ZtSfz9E2fgO1t35/HXtKWxAEgepmOzcuyeaSyeIkyVeF\ndew61gLAinkZ6LTBzwGLJieRkxxFfJT+lNfRi338upGrk4w8eycy6p0YcnUSGRmZ3ngdDhoCs66G\n1LQg4U5djBjFIAgCr68vxeXxM3NsLFOzY1i/vw5zh4v9pa0sn51Gc3tP1QMrOoRpefzP6/vweP1E\nhmpo7/LQ3ObkeFOnNKMMkPHNG2jZ+TWxc+YSNWHiKVM/dh9r4aXPjgFiuTK/AE1Wh+TE8Pr8VDWL\nL6Qz5CiMEYEpIoTaVjvmDicZ8edfO8Hr8/O/n4vfoV1HxQddtUqB1ydQ3tAhbddmE0U5I4YYTtyd\nTrLzSDMAE9KiMPWKQNGqVSyclMjCSUMTnI00aDGGhwRKB3cRG6lDqzl1dZmJpokUm4uJ1sVib3UF\nresyasnPng+ASqslMncckbnjYPnA7YVnZROelU1n1XEaN20clhQwGZmzweFqK4+/XQhAfLSeJ74/\nixH6jigzBHYcbuS1DaVBy77YV8slkxPZebRZStfLzzaRl2nst43EIaYJysiMdEa9E0OuTiLbk+2N\nfHvn0mbNRx/iam3FkJGBafYcnC3N0rruqgQHyswcKDej16q4aUkWfr+fqdkmDh638vaWCtxeH02W\nHidGo9XBl/tr8Xj9TEiL4varcvnw62o2FjVQUN5KepxB2jZy/AQix08A6FP9xNzhpMvlJSXGIDk3\nukPpp2QZiQ4LYVNRA39ad5B/3DuP7cVNrPmqHIC4SB16req8qUSP5Ook59petxBac5tjyPsP5/HZ\nnR7+9uHhoLKnACkxody3YhI/f2k3R2vaeeS1vdx2Va4UiWHQDe17lJ0YjkqpQKtRMi4lipuWZA9Y\n2Weox5eZEI7F5uLJdwrpcHh45OZppMYaTrrPtVnXsq50HT5Vjy2lSoXb70EToue67OtO6zxn3nQz\nuvgEjNOmDbj/+VbYl6uTXDj2BuJ0+uF0+9hW3MTHu6ulZU1WB0WVZvKzY0673TPhQrTnFwS8Xj9a\njQqvz49KqRiyxtTwV7UQWLtVrCSyND+JcamRPPvREWpa7Pz4HztoC+gQadRK7rw6d1BV1QZn98Ib\nv+FErk4ycu11M+qdGDIyMjLdCIJA845tAGTd9B2UajX6hB7NihCT+LC3u0Scrb5mdpqU279kSiJO\nj493tlTy3o6qoHbbOt00WsQw+qX5SUSHhZCXZWJjUQNFlZYBc1B70+nw8OiaA9gcHtJiDSzOS2Tu\n+DgaAu3OGx9HS6+X0X9+eoz9ZT2VFzITz/+Mv4xIt6ZEc5vzFFueXfaUtHK0pr3P8rxME7GROinK\nobKpk398fJSWQHnUcP3QKrikxBh4/t75qFSKQetdDJbM+DD2lbZiCTyobytu5MbF2SfdJ1oXzaqc\nVbxZ9BrdRxKWmUmDpZqbJ99MVEjUafVFqdGSfOVVp7WvjMzZ5O8fHuZQoERmb97ZWsmkDKMstjgI\ndh1t5o1NFXTY3cRE6qT77dRsE/deN2HYr20no9PhQaFQYNCpOVrbRnObk9hIHTctyUalVHDplDa+\nKmyQHBhjEiO4dm4aeq38Widz8XDG3/Yf/vCH6HQ6lEolKnRV4l8AACAASURBVJWKxx9/nM7OTp5+\n+mlaWlqIjY3l/vvvJyysr2DMpk2bePfddwFYuXIlixcvBqCiooJnn30Wt9vN1KlT+d73vodCoWDN\nmjUUFBSQkZHBj370IwC2bNmCzWZj+fKTxILKyMjIAK7WVtxWK2qDgfDsMYAoSjXplw/hsljQBzQy\nalvtAIxNiZT2VSgUXD0zlWSTgRc+OSrVYDfo1NidXkoDOhjdApIT06NQqxRUNNiwdXkIDx34xbDR\n0sU//nNUEgqtbrHz2oYy3t5SgQLxwSnRGCo5VIAgB8accbFcPz/zzE6OzLDRXZWmteP8OjEKKywA\nrF6Qgc8vSM637hK8t1+ZS0ldO+sP1EvfeYWiR+NiKJytKixZCcHOud6/gZOxYswK1h57B6/Cj0ap\nQdCHEBaXyKoJ3zob3ZSROW+U1XdwqMqKTqvilmVjmJptQoGCX7+2j5oWO+/vOM7MsbH8/aPDZCeG\nc8dV4853lwdNu93N2m2VdDq83LJ0zKCFkv1+gT0lLYxJisAU0XM9fvnzEozhIeRlGpk2xoRapcTh\n9rJmQxnbD/dEZfaeMDhQbuaVz0sYnxbFrNzYs+IQWn+gjtYOF+12NxUNHTS1OVEq4Buz0ySdodm5\nsagCehbfuXQM6XFhbD/cxNWzUsnPOrUYsYzMaGNYXHaPPPIIEb3Kjb3//vtMnjyZFStW8P777/P+\n++/zne98J2ifzs5O1q5dy+OPPw7AL3/5S2bMmEFYWBj//Oc/ufPOO8nJyeGxxx6joKCA3NxcKisr\neeqpp3j++eeprq4mISGBTZs28dBDDw3HYcjIyIwynM3N2CoriBg7FvOuXbTs2glA+JicIDHNyNye\nhzqLzUV94KEhJaZv2PqULCN/vXsOu4614PX6KaiwcKDcjNcnhm9GBJwVOq2acSlRHKqycrDKwrzx\n8f32sbLRxuP/LsTl8RMbqeMn10+kptnOxqIGqaqDUiHmN4doVDz4rSm88J8jWDrdxEbq+N1/TSdE\nozrvAksyPcQGHppb2s+fE0MQBErqxO/PnPFxUqQQwJgk8X49Pi2K8WlRTEyP5ndvFgT2Y9ACmueC\n9BM0Rby+wYWtRuuiWZ37Td7y/YsofRytLgs3jL3htKMwZGRGIvtKW3nhE7F85iWTE4LuM7ddmcvj\nbxfy4c5qPtwpppk0WR1cOiVJugaMZNrsbn73xgFaO8Q0twPlZq6cnsKl+YlUt9jJzxIjTFxuHy6P\njzC9+EpzrLaNDQca2F3SQm5KJPetmMhbmyrYcqhRantbcROxkToWTopn66EmWtqdaNVKvr04i7nj\n4iiubsPl8VFa18Gmoga2FjextbiJT/fWEh+lJzZSx6oFGcPi0Kg3d0lpob3xC0jjBjB3Qpz0t1Kp\n4JK8RC7pVf1MRuZi46zEHe3Zs4dHH30UgEsuuYRHH320jxOjoKCAvLw8KUIjLy+PgoICJk6ciMPh\nYOxYUThr0aJF7Nmzh3HjxuHz+RAEAZfLhUql4sMPP+TKK69ErZbDp2RkZPpy7B/P0nm8MmiZQq0h\nfsHCPtsWlJt5bX2pFLYeF6VDp+1fRFCtUjJ/gviw2NBLGwOCRRHzsowcqrJSVGFhSqaJ4iorM3Ji\npJdEp9vHawEB0eljTNx2ZS76EDXJJgNzAqkkOw43SQ4MgNyUSB66MZ8v99exJC9RWi4zcoiNCsz8\ntTulEnfnki/317F2WyUujx99iApTeAgRoVompUczNiWyT9TEmKQIvrUok7e3VJLbK/poJGDQqRmf\nFsWR6jYAHG7foPddMWYF60rX4cCFWqlmxZgVZ6ubMjJnHUEQaLO76bB7aLO7SYsz8PpXZbi9fvKz\njKxaEByNl5sSydWzUvnP7pqg5R/tqub+60deSUyn20dBuRm310+d2U5BhYXWDhehIWo0aiXtdjef\n7avls321gBiZEBulY8OBehxuH5cGUj539IqoOFbbzj1/3xFkZ8XcdLYVN9LS7uTd7WJ0WlqsgbuW\njyfJJIpfzsgRU0vnjo8jP9tIdXMnH++qoabFTk2LGLW26WADGXFhtHd5mJAWRV6mkSjjqcW1T7wn\nlNb3pPz917IxZCVEkBwTSml9B5/traWwwsJl05JJNp1cC0hG5mJjWN7+f//73wNw2WWXsWzZMtrb\n24mOFsNVo6KiaG/vm5NrsVgw9SpRZjQasVgsfZabTCYsFgt6vZ6pU6fyi1/8gsmTJxMaGkpZWRmr\nV68ejkOQkZEZZTgaG4McGPrERNJXriZy4iTU+r5lLzcVNWDpdKPXqshKDOfyaSmDspNg7GlLq1YG\nOT6mZJl4Y2M5hZUW/F+WsrukhcumJXPzEjGn/+UvSqhs6iRMp+YHAQdGbxKNoX0eTEEUjjyVLoDM\n+SM0RC2lGXV0eaQUo3OB2+vnvR1VuDxixEJkqBaFQoFWreBnqycPuN9VM1O5ct4EHJ198+rPNz9f\nNZkv9tfx1uYKHIE0rsEQrYtm5ZiVvHDwBe6cfKcchSFzQeLy+Pjg6yp2HWvB3OHqsz4t1sB9K/qv\ndLV6QQZpcWGolArGJkfws3/uprDCwvEm24ionATiS/32w02s3XqcNrs7aJ0xPIRHbp5KpEFLRUMH\n//zsmDRx0F1StJuvAqXG1SoF+VkmGq1d1LZ2BW1z19XjmDM+jmvmpPHQq3tpsjqYmm3inm+M7zcl\nTqkQ28rPMpEQHcoLnxwlIlSD0+3D4fJxJKA5VG/uYv2Bep55v5grpiXzzUWZ/WpofLSrmv/sruG+\nFRPJSYrgaE0br3whVhb59iVZLJmSJG07PjWK8alRuL1+QjSqYRHrlJEZTZyxE+O3v/0tRqOR9vZ2\nfve735GUlBS0XqEYurLvQFx33XVcd911ADz//PPccMMNbNiwgcLCQtLT01m1alXQ9uvXr2f9+vUA\nPP7443361puTrZMZ+cjjd+Ez3GN4ZNPGoM95t36ftMVLpM+CIFDbYqOovJmcFCNtXeIM71M/XEpO\nSv8lyvpjQpcKvhQfQowR+qDjSEiASZkVHKpslcRCv9xfx89uWkBdq43dx1rQqJQ8cfeljBmCzZGI\n/BsMJjEmnLJaK2jDSEqKGXA7QRB4c8NhYiL0XD4r64ztbimslvRaAEJCtEMbm9iR8WJzImmNbqAC\nVEM7nrsi78IiWLh7wd1E66PPXgdHCBfz77DZaudIlZkFeSmoLuD0uhPH8PkPDvDJHjH6IEyvoTOg\nnQQwd2IyP7x+GnHRA8/SX5+cLP29fK6F97aW8Ie3inj2/stJTzj7kVet7V1EGELQqvuPGly3+Rgv\nfVYCgDFch8XWk4b329suke7HSUlJzM0fi93pYUthDe9sOkJaXCQ3LpvA4eOtvPRxIdnJUfzixjmk\nJ0Ti8/tptnYRHqrFoNP0eRf5/e1hbD9Yy4qFfScQ+mNFUhLL5ozHoNNQb+7k2ff2k5MczeSsWA6U\nNnGwooWj1WY+3VuLxe7nN99fKEVddjk9fF1cx7ptxwF44t9FQW0rFLB0Vi5J52A8ZAbHxXwtvVA4\nYyeG0SheXCIjI5k5cyZlZWVERkZitVqJjo7GarUG6WX03u/w4cPSZ4vFwoQJEzAajZjNPYJ1ZrNZ\nstFNZWUlgiCQlJTEm2++ycMPP8xzzz1HQ0MDiYk9+WHLli1j2bJl0uf6+vp+jyEpKWnAdcNNd976\nuSpHM9rtgTx+F7K9boZ7DFv37qH0zX8FLXMoVTQ2NuL3+xEEgWc/OsLe0lYAjGFaulyiE0Nw2aiv\nH7yWgdrXMzMWoVdJx9F9Lq+ekcihytagfTbtOSoJKU7PMWFQOs/4+M/X2MG5+Q1eaL+FKL34wH6k\nrJZIjTi76PX5MXe4UCjECiZKhYJ6cxevfnoQgDHxWnSaM3v5+nDrEQCm58RQ1WTjxkXpgx6bszmO\nZ3o+nV1iqWFLm21Qfext74FJD+CwOnBYHafY6/Q5n7+/bs7W+F0ov70/vFVASV0HU7KMXDM7jayE\n8EHpu5yPsfMLAhUNNqLDtJLwJIhjWH68Gr1WjV8Q2Hm0mXe3HAPgJysmkpdlRKlQcOi4Ba1axdiU\nSLyOduodfSOeu+l9fEsmGdl+UEdzm5O/r9s1pLSSenMXnQ4POckR+ANBAap+zm+3vZa2Lt7YVMG+\n0lZUSgXpcWFkJYaTnRhBfJSOmhY7mw82UhEoI/6dS8dwaX4iVpsLpUKBUqkY8N44LSOUabdOD9jz\nsmBcFHNyFojRD3479fV2adsOF3T0czxq4JIJ0VjNzQwl/qwDUAA/Wp4TWCKQND2O5dPjaOxU8ptX\nt7LrSD1/eG0z3wxEUj6yZj8WW98omvgoHRPTo7l2ThqaE/rdzYXy+7tQ7A2G4byWnsvjGy1jN1gH\n0hk5MZxOMd9Xr9fjdDopKipi9erVzJgxg82bN7NixQo2b97MzJkz++ybn5/Pm2++SWdnJwCFhYXc\ndNNNhIWFodfrKSkpIScnhy1btnDllVcG7fv2229zxx134PP5pBOnUChwufpeIGRkZC4uOo9XcuzZ\nv/VZHhJwhna5vFKOrFolPoB162DotCoMuqFdFqPCelIF+hNLG58aRW5KpCTSCbD9cBMer3jtykmW\nZ15GI1KZ1YC4Z1GlhX9tLKcp8CJ9xfRkblycTWWTTdpnQ0Edy2emnrZNq83FweNWVEoFty7LOWlF\nnAuN7tKBBRUW9pe1Mm3MwNEtMhcfNS12SurEV9XCCguFFRaSTKHccVUuScZQtCfRDnK4vXh9AqFa\n5TnRr/F4/Tz38REOlJtRKRXcsnQMCyclUFhp4dY/bQFETSalQkFj4HoxNjmC/OyeVOtJGacXuRcR\nquVXN+bz00BaSWGFhbzM6FMed6PVwX+/vk8SsNZpVSgVCu64KjeoX26vn39vKWd/Wav00q5WKfD5\nBCoabVQ02lh/oO/L4bcvyWLZVPHFpbdTZyicyxKoAzFtbAK3XZHL3z86zJaDjew51oKAqPeREK1n\n2dQk5k2Ip6LBRnpc2Ki6RsvInGvOyInR3t7OU089BYDP52PBggXk5+eTnZ3N008/zVdffSWVWAUo\nLy/nyy+/5K677iIsLIxVq1bx4IMPArB69WpJ5PO2227jueeew+12k5+fz9SpUyWbu3fvJisrS4rO\nSE9P56c//Snp6elkZGScyeHIyMiMAhxNTf0u10aJ+fCHjvfMuSzOS6Su1S7ltcZG6ob8EKtUKCQn\nxYKJCX3WKxQKVs7P4PG3CwkN6CQcKDPjCVRZGJM48lXiZYZOXGSPuGdBuZln3i8OWv/F/joWTEyg\nsrHHibF2SyVjkyKCHFser58/v3eImPAQfnBl7klt7jjSjCDA1DGmUfdwrA/peQn96weHefWni85j\nb2RGGhsLxRfjSRnRRBm07D7WQr25i0fXHECjVnL38nGS46umxU5ru5OpY0y0djj579f20+XykhEf\nxs9XT8ZwGiWGB4PD5cXnF3jx02MUVYrlj31+gVe+LOW1DWX4/D2aB81twdGAi4exCkVEqJapWSZ2\nl7Tw9HuHSIkxoFIqsHW5uWxaMkvzk/j/7N15fFTV+fjxz50lySSTbSb7ShbCEnbCIovI4oKg4q7g\nVutWrVjb2spPq/ZrrW0palu1altxqbuISkVBRHADgUDYCYRAyEr2PZPZ7u+PSQZCEggw2Ybn/Xr1\nVTJz5z7nnid3zJw55zw1jTbCgnxRFIUDhTW8vuaAewADXB/KwbWv06LrR2Lw0bI1p4I3vspxH+Pn\noyUuLICfXDiQ0EBfDpfUkVNcR25xLWU1FqJN/lhsDlKjg7gko2t7UPUHYweG8eQtY3n/m1x2HDr2\n98ZPL05zv7cPG+D9S9uE6G5nNYgRGRnJ4sWL2z0eGBjIY4891u7xlJQUUlKObUY3Y8YMZsyY0eFx\nS5Ys6TDm+PHjGT9+vPvnW2655UyaLoTwUraaave/U277CQdfWwqApqWKUWvZSYA54+P5YkuBexAj\n7Ay/Abr/8qE0NtuJCGm/YSi4dol/4qYxBAfoWbR0C3Uta5oz0sJIiJAdx71R60yMsloLe1oqa0xN\nj+TWCwfyzrpcvsoq4q2vc3C2fHCJDfOnsLyR19ccYMGMVPYX1HDZxAQ27it1V+a4aWbqSavRtC6P\nmnRcKT5v0ToTo5XTqfapUrCi9zRZ7e6KFDdOSyY2LICbZ6by/jeH+CqrCJvdyT8+2cPM0TEowPqd\nJVhbZsJpFFcpSwU4fLSed9fn8tOLTz5Y2BU1DVY2ZZe5ZvYpkBhh5Pf/3eaOa/TT8ZtrR5Bf1sCn\nG/M4esKgxU8vTsMU6Euo0ZfS6iZGJnt2z6RLxsWRU1xLbaPVvbQR4L1vDvHpj0doanaQGhNEgJ+O\n7bmuAZewIF8uyYijusHKxMERLF29n4PFdSxauqXd+X9++VDGpJrbzI4YmhjK0MRz48N7XFgAv7xq\nON/tLuG/Xx1k1ugYmXUphIedU7VJNSfZ6Olkz/VUGyRe34/r7f3ZW/nzZGxrlesD34Drrif6ghk0\nl5YREB/vPv/BYtc334uuH4k5yEBcmNH92vBgvzNqR1CAL0EBvm0eO/E8SS0zLkalmNmwt5TLJiZw\n9ZSOdzA/E72Zu56I39/uhchQV6m+8hoLQS2zItIHmPDR67hmahI/ZpeyL7+G1uw/eNUI/vJ+FgXl\nje5N3/x8dHyx5Vh5xI++z2PBjNQO4+3Oq+JQSR0+Og3Dk8xn3P7u6uezPa//Cd+OF1Q0nrS6Qn/7\nfelMs9WBbyelnnuqHd11bXvyqlCB5KjANhsrnm68TdnlWGwOBsUFEx/h+p0w+Gq49cI0rp6SxNLV\n+9m8v6zDZQxOFVKig7j2/GSWfLidb3cdZXiSmYmD2w4E1jfZ+M+qbEalmJk2vONZEXaHk+yCGrYd\nLGfD3lLqGo9twOmj07gHMJKiArlr9mBiwwIYEBXE1OHRWG0OaptsRISHU1ZW1mZJRVy4sV2s09FR\nf6bGBPPcPedhdzj58NtDrNx87H2mqWV/qJwi1/IcvVbh0vEJzJ2Q0GYQ9d7LhvKn97bT2GxHq1Ew\n+OgYkWxiZLKZUSlhPb4uv684vj3nD49h0tAodNozb6O3vJf1lXhd5al29eT1nWu58/pBjC1btpCZ\nmcndd9/d200RQvQAa5XrWyPfUBOKopB0/Q3u55yqSmGF61unhAjXH4aRocdmT7R+e96dfnrJIK6e\nktTprA3hHcxBrkGtiloLIS0lVlv3Twnw03Pt1GSWrt6PimvadWSIgVsvHMTiD7a7z/HOuoNtzrkq\ns4DJ6ZHtPrx/u6uYV1e5dvc/f3j0SWdr9FeBBj1xYQHub42zC2r6TInIs2V3OPlyayFB/nomDY1E\nURRUVeWttTms3lrIkIQQHpg3DP8uVFDoL1ZnFvDfta6lB1qNQnpiKDNHxzAq2bW/Quv1B/jpmDdp\nQKfnKa+1sKNlpkBHy/mMBj33zBnCiCQTNY1WtBqFUKMvB4triQsLYHJ6JH4+rgGyG6en8saaA/z7\ni3346jSMTg2jur6ZrTkVfLmtgMLyRjIPlBPkr2d0imtpSl2jlR2HKtl2sIKdhyppallm0So9MZTy\nWot7L5yfXz6U8YPaz5Ty0WsJ02uJCA3A2VzX7vnuotNquG5aMkMSQogPN7LzcCWpMUFoNQpvfHmA\nxmY7d7YMuJwoPNjAkrsmtnu8tz/Y9DVnM4AhhOic9/wXsRMZGRlkZGQAJ989tad3xZV4Ek/idU/M\n5krXH7T6kBDeX3+Q7/Yc5f9uHkOI0Y/yWgtWm5Mgfz0GHy1Op5Pw4GMzKMyBvh6/9hPPp9MohAV5\nPk5n8XpKT8XtL/eCTqMQ0LIHSlFlIwBBBr37fFPTI1mbVUReaT0xJn9UVWX4gFCMfjrqLcdKpBp8\ntExJj+TLlm+RP9+cT1iwH5OHRhIZ4sdHP+SxYuMRAC7JiOO685POqo+6u3/P5vz/d/MYvt1dwtLV\nB9iXX82Fo0+9g3lv/74UlDfwr8+zGTswjBkjozEa2s4oqapv5oUVe93felvtDqYNj+ZAYQ2rtxYC\nsPdINU+/m8Wl4+IYnWI+6SaV3Xm9njz3d7tL3P9WVZUdhyrd+0RkDAzj0vHxrMp0lRWdPiK6wz1e\n1u0o5rWW8tYAA2MCO2yjVgNTh0W2eWzi4HD3v1tfM31EFLsPV5KZU8Gzy3ehUUAFVLXNS3ll5T4u\nn5jA/oIasnIr2+xlEWv2Z2SymdEpJlKig9BoFJptDj7deIS6Rhujkk2n7Mfe+G/D8JY9GqamH+un\nX18z/Kza1Nv3Xm/xlv+2e3u8U+nuvwW707mSO68fxBBCnDucdjsNBa4/fLWhYaxZvR+LzcFfPtjB\noutHUVTh+jAZbfJ3v6b1W3JwfdsrhKcYfLQ0WOw0tAxKHF/JRqNRuGVWKs98tIuMgccqbfifMIhx\n64UDGZNipqBlA9oNe11r//NL6/Hz0bJxXxmKAjfPSGXGKO+ua6/RKAyKc23Qm3mgnB/2HqWytplL\nx8eTX9rAd7tLuHpKEn6nsfyiu/37i2zySuvJK60nK7eCx+a7NiovrW5i474y1mwrpPa4ZQebssvw\n0Wl5eeU+AMammsktqSOvtJ5/fraPa6YMYO6EhA5j1TY0k1NUi8FH2+E3573JaneSdbCClOhAggN8\n3DNq/vnzSdgcTtbtKGH594dRce3tsvNwpfu1f/lwB0/cNMZdzlNVVb7bfZS3vj42U0mnVdrMqjsT\niqJw5+zBaFZls3l/OU7VNUtkUHwwvnotM0ZFsyqzkF2Hq3hnXa77dUMTQhidYmZksqnDGXa+ei3X\nTk06q7YJIYRoSwYxhBBeo+5gDo6mRgzR0eTUa7DYXFN7C8obue+FHwhu+TYv7rg/8BVFYcbIaA6V\n1JEU5R3T00Xf4Frn7yoz6KPTYDjhw3VKdBD/uPe8NvuiaI/brPKeSwe71+YvvCKd5z7ejc3hJLe4\njqyWKfR+ei0/mzvE4xv/9VWRIceWfL2yMhuA0EBf3lp7kMZmO812J7dflNZbzWtjT14Vh4/Wu3/O\nLa7j8y0FXDwmluc/3cORMtcH+cHxwdw8M5VHX8tkd141u/OObU48e1w8Bl8tj7yW6TrnkeoOBzFK\nq5v41b++oKLWtWzhN9cMP6tNFB1Olbomm/s982xsyi7jza9y3BsaD4kPxu5QiQzxw+CrwwBcPjGB\npCgjf/t4N3aHSrPt2Dd7+WUNvLoqm5tmpLI3v5rPNxdwoGXmSlpsEH4+WtITT10mtCv8fLT8bM4Q\nkqML8dNrGJcW3mb2TGKEkd+9sZWaBldZ7vsuG8K4tPDOTieEEKKbyCCGEMJr1Ga7vr0MSR/O1znl\n7Z6vabSRGhPE3AnxbR6/ZdbAHmmfOLccv4dBcIBPhx+yTtzYVXvcevKJQ46tnTf46lh0/Uicqsrt\nz3zrfnzRDSNJjDi7jf/6E+W4ksatKmotNDa7Zq9kHazoraa1oaoqH353GIArJyXyzc4SKuqaeW99\nLpuyyzhS1oCiuAaqMtLC3ftC7MpzlWQcHB/M1PQoUmNcGwI/e/cEHnz5R/YcqeazTfkMigsm80A5\niRFGBsYG8ecPdlBR2+yOn11Qc0aDGA6nSlFFIx99f5htBysIDvBhYEwQF2fEMTDm9MtB5xTV8srn\n+9qU52ytBjUkIaTNscMHmPjXA1M4Wm0h0N8HnQbeWnuQb3aV8P2eUr5vqUACrsG7m2emMmlohEcG\nL46n0SjM7qTkZ5C/D//v+pEUVzYyMtnk8dhCCCG6RgYxhBBeo3UpiSEhgaydle2ev3P2YCYNCZc/\nPEWPOH7mxYl7IXRGe4qyoRpFYWyqmcycCu6/fOg5NYDR6uaZqTz6eqb75+OrQNQ22nCqKr29ld7+\nwhpyS+oI8tdzSUYc/r469/KHQyWujRvDgvyYcFwVjBunJ/P3T/YwKtnEDdOS27xPhRp9iQ8PIL+s\ngQ++PdQmlp9ei8XmYHCCmfEDQ3njqxz3Piyn69MNeXzSsscKuEqFbjlQTlZuBb+9dkSXy0RW1Tez\ncW8pqzILsTtULhgRzYLpKXz43SGcTpX0xFCGDWg/yKIoCjFm10w5p9PJ7RenMXNUDP/6IpuC8gaC\n/PVcOi6eqcMiCfDrneV/kaGGs166IoQQ4uycU4MYUmLV++L1dFxv78/+XmK1sdA1iHHUEEld09E2\nzz1z93lEhBi8tuxbb+8ILyVW2zu+LGigQd+l/wYNTzKRV1pPtMnQ6fF3zB7MlbXN7go7ntRXS6we\nLyEikJ/NHcI//7cXgN1Hqts8X1VnpaLeSoCvjvjwntkb4sTr23HINaNi8tBIDL56Lhobx8QhkWg0\nCvc9/z0ANY3WNq+LDw9k8R0TOo1x88yB/HXZDhwOFaOfjpqWwRuLzUFCeABP3TmNXfvzACiqbDyj\nPs8tOVYZ4965Q0iMDGTFxiN8t7uEf32ezZO3ZWDwaf+n49qsIhQFpo+MoaLWwpNvZ1FZ55oZMjg+\nmFtmDUSn1bBgxqlnvXVUnvr/bhnLtoMVDIoNJui4fYw8obffO0/k6fb0x/fOvhzvVCR/fTteV0mJ\n1b4X70ReP4ghJVaF8H72pkaKvvySpuJiUBQ2lrj2whgQaXSvSTcF+p7sFEJ4nL/vcTMx/Lr2n9t5\n5yUSEuDD2OM2+zxRgJ++176F7ivOGxJJbaONt9bmuDfsbfWrf/0IuPY3eP7eSSet5nEyq7cW8L+N\nRxg/KJzLJiYSfMKHZ6dT5fDROgorGshIi3DnRFVVtrUsaxnRUjJUURT36687P5n3v8nlmimnt9nj\n4PgQnr93Er56LWpLfKdTJaeolqToQAL9fYgx+aNRoKiikYKyeuLCT2+gq6Jl4OHRG0eTFueadXHH\n7MHkl7k2J33764NcNXkAL3+2F51WgynQl7351e4Sog6HypfbCqmsayY5KpDJ6ZFMGRZ11mUmdVqN\n7D0hhBDCzesHMaTEqsSTeH0/3tnG3P3cs9Tuc30rDgWe+wAAIABJREFUq5t6MRuzy9FpFeZOSOD5\nT/cAoFFcMby9L6XEat+J53fch+eA48qrnoxOqzCrpXRof7sPe/r804ZF8vX2IuqbbIxMMnG4tJ78\nls0yASxWB9UNzYQF+Z3kLB0rqWriv1/lALB6ayFajcL105Ldz3/8Qx6rthbQ1OwaMN2XX8Odswfj\ndDo5UFhDUUUjgQZ9h2U/Z2fEkp4YQlxYwGn3h49Og9pS81OjgEarMDj+2BIPvU5h2ohovt5ezKur\n93P7RWms21FMVKiBffk1VDc0c/PMgQT66zlQWEN5bTPThkfh76tDVVXKaiwAxJqPzVrTaDTcfelg\nHnszk/U7itlfUE1xZVOH7XvjK1fJ07gwf3519TD3wI6U6Ow6KdHZP+J1RvLXP+KdipRY7bvxWnn9\nIIYQwrvZGxqo3bcXjV7PkAd/xSF9BHyyh6EJIWQMDOPmmalEyfpl0QsMx23s2dWZGKLrfPRa/nhb\nBqqqoigKb3190D2IER8WQH55Aw1NdsJOYz/K6vpmDh+t58uthW0eP1hc6/53VX0zn27Mw6lCeLAf\nZTUWfswu5aaZqRRXNPBSS3nUqZ3MQFAUpVv3MrlmShJbcyrIKarl/722pd3zv3sjs83Pm7LLmDQk\ngsZmOza7k0CDvs3vLkBcuJFrpiTx7vrcNgMYl2TEufqg2sIXma7lfEH+en519fBzfraQEEKI7iN/\nVQkh+rX6PNca8ICEBEKGDKV6exEAIQGu5SMzR8X0WtvEuc3ge/obe4rT17oB5tzx8dQ2WJk9Lo73\nvnFtfllvsZ3spW04nSp/+XCne3lKgJ+OiYMj+CqrCL+WfSDsDidLlu3CqcLoFDMPzEvnD29nkVNc\ny/odxXyyIY8Gi53kqEAun9i+FGpPCPDTsWB6Ci+27BkCoNdpmDQkgn0FNe6lH2FBvpTXNnOopM69\n2ShAjNm/w/NeNDaW7bkV7M2vIT48gEXXj2xTgcfPR0tmTjn3zR1CqFGW7wkhhOg+MoghhOjXag/s\nByAgIRGA6gYrAMFGz27+JsTpCvY/9jsYIDMxul1wgA8/mzsEODbzpcFi7/Lrt+dWttlf44ZpyUSF\nGvgqq4iGlsGQkqomCspdsz2umux6zxkcH0xOcS1vt1QfGZls4ueXDUWv671Nz8alhfHzy4ei4Bps\nURTXYE+T1c7arGKMfjqmjYhmx6FK1u0oxuCrI8BXR6jRh4y0jvdj0SgKC69IZ8ehSkYmm/HzabvX\nyLxJicyblNgDVyeEEOJcd079VSXVSbwvXk/H9fb+7G/VSRoK8ilc+T8ATCNHodFoqG1wfdgwGX3b\nnNPb+7K3d4mW6iTtjUwxExHsR2mNhbgwY5/4b9Cp9IfqJF1hNLgGkBqb7V2OnVfm2gR4zvh4LpuY\niL+vjqIK14BFg8V1nqp61yDp0IQQEiNd61TS4kJgUz4ACRFG7rtsKL4dVPDoCcdf6/hBEe2eD/Dz\n4bKJxwYaRqWEMSql801kTzxngMGH84ZGeaClXYvXE/rKvddKqlv07XinIvnr2/G6SqqT9L14J/L6\nQQypTiKE9zr43zdxWq1ETpmKefQYAKpaZmKEyEwM0ct8dFr+ePs4SqstxIX1TKlP4dK6fKe+qe1M\njDXbCtmeW8FdswcT6N/2PaKkZZlFjNnfvUzC2LKvQ+uMjtayoebjNgsdmhjCuLRwtBqFG6enuJee\nCCGEEKJ7eP1/aaU6icSTeH0/3pnEtNXXU7NvL4pWy4Ab57tfX9XyISPYv+NqEN7el1KdpG/F02kU\nYkyGLp+nt3do70/VSU6mtbxtXZMVq82OTqvhrbU5fLnNtWfOoqWbSY4KJCzYj7AgP8KC/TjSUo45\nItjP3U4/H03LeWxYrHYqal3VO0KNPu5jdBqF+69Id19fb+awO2P3t3uvr8frjFS36B/xOiP56x/x\nTkWqk/TdeK28fhBDCOGdKjK3gKoSNGgQOn/Xt9z1TTaOlNWj1ShEmTrenE4I4f1aZ2KsyixkzbYi\npo+MZk3LAAZAbaONrNzKDl8bFXrsveP46iJ/fDeL2JYZNaZA2bhSCCGE6C1nPIhRXl7OCy+8QHV1\nNYqiMGvWLC699FLef/99vvrqK4KCXGtFb7zxRsaMGdPu9VlZWSxduhSn08nMmTOZN28eAKWlpTz3\n3HPU1dWRnJzM/fffj06n4/PPP2fNmjWEhYXx0EMPodPp2LdvHxs3buS2224708sQQvRDTrudgs9W\nABAx5Xz349sPVaKqMDghuM2u+UKIc0tSZKD73w6n2mYA4xfz0gkx+lBe20x5jYWyGgvltRYqai0k\nRwdhNHT83nH4aD2HW2ZryCCGEEII0XvO+K98rVbLzTffTHJyMk1NTTz88MOMGDECgDlz5nD55Zd3\n+lqn08l//vMfHn30UcxmM4sWLSIjI4O4uDj++9//MmfOHCZPnswrr7zC2rVrueiii/juu+9YvHgx\ny5cvJysri7Fjx7Js2TIeeOCBM70EIUQfV7VjO1U7d2LOyCBoYBpKyyZCpd9/S3NZGYboaMInTHQf\nX1Dm2oQvLTa4V9orhOgbEiKMnDckgg17S9s8fsV5CYxKMQMw4LiBjpOZMCicH7PL2jyW1MXXCiGE\nEMLzznhb0dDQUJKTkwEwGAzExsZSWdnx1MwT5eTkEBUVRWRkJDqdjkmTJrF582ZUVWX37t1MnOj6\nUHLBBRewefNmAFRVxeFw0NzcjE6n49tvv2XUqFEYjcYzvQQhRB9WsTWTPc8uoXjNanb96Y9s/uUD\nHP7gfRzNzRSs+BSA+CuudA9sAJS1rFePCDH0SpuFEH3HoLgQ979njIwmPNiPCR1U7DiVu+cM5p8/\nn4ROq7gfC/TXe6SNQgghhDh9HqmNUlpayqFDh0hNTQVg1apV/PrXv+bFF1+kvr6+3fGVlZWYzWb3\nz2azmcrKSurq6vD390erdW3IZTKZ3AMjl1xyCY888gjl5eUMGjSIr7/+mosvvtgTzRdC9DF1ubns\n+8ff3D/7RURgq6mhcOX/2PXnp2muqMA/NpawcePbvK68xjWIER7shxDi3BZtOjaYOX96CovvGE+M\n+fT3ytEoCgZfHQ9fN5JAg56bZqR4splCCCGEOE1nvWjcYrGwZMkSbrvtNvz9/bnooou45pprAHjv\nvfd44403uPfee8+6oeeffz7nn+9a+/7hhx8ye/ZssrKyWL9+PWazmVtuuaVdvdo1a9awZs0aAP70\npz8RExPT6flP9pzo+yR//Z/JYKAyex/R48azb/Gf3Y9P/cMficwYR96aL9n8179QfygXgEHzriI2\nLs59XLPNTkWtq7zqsLRETEEyG6MnyT3oHbwpj6HmMKLX5BAfEURCfNypX3AKMTExnJ8x2AMt6z7e\nlL9zleSwf5P8eQfJY993VoMYdrudJUuWMHXqVCZMmABASMix6ZszZ87kz3/+c7vXmUwmKioq3D9X\nVFRgMpkIDAyksbERh8OBVqulsrISk8nU5rWVlZXk5ORwzTXX8Pjjj/P444+zbNkydu3a5d6To9Ws\nWbOYNWuW++eioiI6EhMT0+lzntY60NJT5Wi8PR5I/vpzPABHczO+tTX8+MxfsZSUuB/XBwUx5um/\n4PT3p7i4GP2QoUReMJ2j69fhExKKfvAQd97fW5/LmqwibHYnvnoNTXWVFNUrbeJ4e1/2Ru5a9cQ9\n6O392Zv5a9Wdeeyt/vzjrWNQFMXrfj870l358/Z7oS/krlV35NDb+1Py51neHq8rPJnHnrw+b8ld\nVweQzngQQ1VVXnrpJWJjY5k7d6778aqqKkJDQwHYtGkT8fHx7V6bkpJCcXExpaWlmEwmfvjhBxYu\nXIiiKKSnp7Nx40YmT57MunXryMjIaPPa9957j+uuuw4Aq9X1rauiKDQ3N5/ppQgheom1ppptjyzC\n3tDQ7rnEq69F539s6rei0ZB6609Inr8ARatz74XR1GxnVWYBThUSwgO4cEwsiqK0O58Q4twj7wVC\nCCGE9znjQYzs7Gy++eYbEhISeOihhwBXOdXvv/+ew4cPoygK4eHh3HXXXYBrBsXLL7/MokWL0Gq1\n3H777Tz11FM4nU6mT5/uHuxYsGABzz33HO+++y5JSUnMmDHDHfPQoUMA7g1Fp0yZwq9//WvMZjNX\nXHHFmV6KEKKXlP+4EXtDA4bwcEJGjCTy/AuozTmAvbGBiClTO3yNRu/T5ucDRbU4VUiNDuLR+aN6\notlCCCGEEEKIXqKoqqr2diN6iiwn8b54IPnrC/GcNhtV27NoLCok+sKL0Rm6th/FjqeepC7nABMX\nPYI2bdBptxfgrbU5fLmtiDnj47l2alKnx/WXvuwv8Y4ny0n6X7yOeONyEm+N1xFZTtI/4p2MLEfo\n+/FORvLX9+N1hSwn6d143b6cpD86cePPrj7XU22QeH0/rrf3Z1fiqapK/aFcag8epCHvMPV5h2ks\nLER1OADI//QT/OPi0BkMhI4YRdylczqc0t1cWUldzgE0ej3REyZSXlNz2u212Z1s2FcKwPhBEX3i\nHj9X4vV0fG/vz97OX6vuaoe396c358/b+7Kv5K6Vp9vj7f0p+fMsb4/XVZ5qV09e37mWO68fxNiy\nZQuZmZncfffdvd0UIfqtxuIimoqLaSwspCJrG3U5B9oeoCj4hIRgra5GdThoyMsDoGbfPurzDtNU\nXIRPcDBDH/glGr0egPItmwEIHTHSNXPjDAYxth0sp77JTkJ4AAMijWd3kUIIIYQQQog+z+sHMTIy\nMtybg55suktPT2OSeBKvr8VrLC6iPicHa00NUTNnUbF5E75mM8bkFLJ+/ziOpib3sVqDAfPYDIwD\nkghITCQgPgGtry8A9sZGavbtJW/ZhzQVFVL+40YAGoBD779L0o0LACjf9CMA5oxxZ3yN63YUAzB1\nWBSqqtKV1XHemLvejNfTcb29P3t7Sm13x/f2/vTm/Hl7X/Z27lp1Vzu8vT8lfxLPkzzdnp68vnMl\nd14/iCGEaK/sx40Ur/kSe2MjzuZmmivK2zyft+wD1z8UBfPYDPcARuS06YQMG0bI0PQ2lUOOp/P3\nxzxmLOYxYynd8AO1+7PR+QdQuPJ/FK1eRdCgwQQNTKM25wCKTk/oyDPbjLOi1sLuw1XotArnDYk4\no3MIIYQQQggh+hcZxBDiHGMpLyfn1X/jbClRfLzQ4cOp2rnz2AOqSkXLso+kBTcRM+ui04oVcd4k\nIs6bBIDeaOTw+++y7x9/I3joUFBVAlNTu7wJ6Ik+3pCHCoxNDcNo0J/ROYQQQgghhBD9iwxiCHEO\nUZ1Osv/5Ak6rFdOYsSRceTWqw87R9evwCTWRcPkVHPjPv2iurGTQz+7jyPJlFH+1Bl9zGBGTOy55\n2lXRsy6k7mAOFVszqdmzB4DgQSevSKKqKg6nik7bdvOg7IIavt11FJ1W4cpJiWfVLiGEEEIIIUT/\nIYMYQngJ1enEUnoUfVBwp0s9KrdtpT73ID4hoaT+5Kfoja7NMI233AaAoiik3XGXe31b0vybCB4y\nFGNS8hnPmGil0esZ/POFNOTnk7fsfRqOHCFswnknfc1/Vu1ny/5ypo2IYkp6FHFh/jicKm+scW0s\nOmd8PFGmjq9VCCGEEEII4X3OqUGMvlB+0dvL30iJ1e6J57BaKf5qDU3FRUROPR9j4gDyP/sfjqZG\nFK2W5qoqqnfvwlZb635t8OAhBA8aTNycuWh9fbE3NJC/4hMA4uZehm9QUKfxjnuA8HHjPXpNgYmJ\nDPvlQyeN7VRVXv5sLxv2usqnrsosZFVmIQMijUwfGUNhRSMRIX5cNjGxyznx9nuht0tdSYnV/hWv\nM1JitX/E64yUWO378U5FSnT27XinIvnr2/G6Skqs9r14J/L6QQwpsSr6O9XpZN/zf6dyexYAFVu3\nYoiJoTZ7X7tjFZ0O1W4HoGbfXmr27aV8y2YCEhIo37wJ1W5HHxxM1LQLevISTtv6HcXuAQyAyemR\nbM+t4PDRepau3g+4KpL46LS91UQhhBBCCCFEL/D6QQwpsSrx+mM81emksaiIo+u+pvirLwFXWVNH\nUxO2ulps2bVo/fxwWK3gdGKIjmbwfQsxREdTuPIzbPV1GBMHsP9fL9NYWEBjYQEAwUOHknjVtSg6\nXZ+5H2obrZTllpJ75Ch6nYZYsz/vrj8IQFKkkQeuHEZIgA8lVU08+voW7A5XGdURSaYzaqe3/a70\ndryejuvt/dnbZeakxGr/iteT8b29L3s7d62kRGf/iNcZyV//iHcqUmK178Zr5fWDGEL0N067nd1L\nFlO7b2+bx4c88CC12fs4svwjAhISGbLwAXxCQjn63TeEDB2GX3g44Foq0spaXc3h998FIOXWnxB1\nwfSeu5AuKKux8P9e24LN3v4NcGSyiV/MS0dRFACiQg08vmA0W3MqCAv2IzHC2NPNFUIIIYQQQvQy\nGcQQoo/JX/FJuwGMwfc/QPCgwQSlDSJ61oVoDf7HPtxP63xgInb2pURMmUrdwRxCR47yeFsbLDay\nC2rYm1/Dvvxqmm0O7po9mNSYIGx2JxqNglajdPr6DXtLsdmdRIT6ExXix+GjddQ22gg06LllZqr7\nGlvFhxuJD5fBCyGEEEIIIc5VMoghRB9Se2A/BSs+BUVh8M8XotrthGWMg5bNcxRFQecfcFrn1AcG\nYho1us1jxZWNZB2swOCrI9CgZ2hiCAafzt8ObHanu9xpdmEN+47UsDe/miOl9agnHPuHd7Lw0Wmw\n2p3EmPyZOzGe7PwaQow+zDsv0T0wUdto5ausIgDuvyqD+BBXSVW7Q0UFfHR9c7MnIYQQQgghRO85\npwYxpDqJ98Xr6bjdGcdpt5Oz9FVQVeLmXEZ4xjh3PE+uN7PaHTzz0S7KaiztnvPRaQg06Fk4bxgA\nRj8doYG+PPp6JmU1TaiAetyohVajkBoTxJD4EFJjg9iwp5RtB8tpbHYAUFTZyCsrs93HR4T4M3VY\nFOCqOFLTYCUtNpiMwVGUlbo28tR2016d3n4v9PYu0VKdpH/F64xUJ+kf8Toj1Un6frxTkeoWfTve\nqUj++na8rpLqJH0v3om8fhBDqpOI/qIyaxtNxUUYIqNIvPKqbovz7rpcymosRIT4MTg+hF2Hq6is\nawbAandSUdfME//NRFXBz0fLFRMTOVrdBLgGLZKjAxmSEMKQhFBSY4Lw1R8bdRiRZMbucJJ1sIIN\ne0vd522w2CipamLp6mwSwgOIDzfy3a4SAK6floy2j/5HTAghhBBCCNG3eP0ghlQn6Xo8VVVx2mw4\nLRb0QUHdHs+TvCFexbatAERMmQpabZsYTqeTxmY7Bh9tu30ijh2j0mCxYzToOj0mu6CGNdsK0WkV\n7rl0MMnRQTRZ7azclI+/r47U2GCeeifLPdvCYnXw3je5AFw8NparpyS1W+ZxYl9oFBiTamZMqtn9\nmKqqvPblAdbvLOHp97YzOT2SmkYbESF+JEcZOzxPd/GG35W+FK+n43p7f/b2Du1SnaR/xevJ+N7e\nl72du1ZS3aJ/xOuM5K9/xDsVqU7Sd+O18vpBDHFyjuZmrDXVFK1axdFv1qPabYCrwkXi1df2WDtU\nh4P9/34Fa0UFTrsdp7WZtHvuIyAursfa0Juq9+ym9PvvAAgdMbLd8yt+PMKy7w6THB3IrTMHEhlq\n4NONR/DVa0iIMLLrcBWb95e5N8VMjDRywYhoxqaa2wxofLwhD4A54+JJjnYNVBl8dFw9JanlCAVz\nkC81DVZuvCCFH/eVsr+wFgWYNTr2jPepUBSF66clc6ikjiNlDXy5tRBwlUntbMBFCCGEEEIIIU7U\nbYMYWVlZLF26FKfTycyZM5k3b16b5202G88//zy5ubkEBgbyi1/8goiICACWL1/O2rVr0Wg0/OQn\nP2HUqFHU1tayePFiGhsbuf766xk/fjwAf/nLX7jjjjswmUzddSleSVVVcpb+h9Jvv+nw+aLVq4id\nfelpbyJ5Jqw11ez7x9+pO5jT5vFD7/yX9F/9BsULlxo4mps59M7blP24AWN8ApayMlBVIi+YTkBC\nAuCaBfHyyt1sO1jhfl1ucR1PvZtFVKiBI2UNHZ67rsnGrsNV7DpcxcCYIO6eM5iSyiZW/HiE7IIa\n/PRaLs7oeHBIo1F44qaxWG12zEF+TBwczvIf8hiRZCI82O+srtnfV8cTN48h80A5y747TGl1ExMH\nR5zVOYUQQgghhBDnlm4ZxHA6nfznP//h0UcfxWw2s2jRIjIyMog77lv1tWvXEhAQwD/+8Q++//57\n3nrrLR588EEKCgr44YcfeOaZZ6iqquLJJ5/kb3/7G9999x0XXnghEyZM4Omnn2b8+PFs2bKFAQMG\nyABGC1VVaSouoqmkhMDUgficZElI4Wf/azOAEZI+DGXwSOo2/YCtuACn1Urhqi9IvPLqbm1zQ0EB\ne59bQnOF64N6xOQphI4YSfY/X6Bmzx6yHv8dcXMvI3zCxG5tR0+yNzVx8LVXKd/0I+CqSALgExpK\n8vwFAKzZVsR/17Yd1LlhWjKfbymgpsHabgBDp1V49MZRRIYY+O/XB9mXX01js50DRbX8+l+b3Mf5\n6bXMn56Cv2/nt35wgA9Op+v5AD89N81IPfuLbqFRFMalhTM2NYwmq50AP73Hzi2EEEIIIYTwft0y\niJGTk0NUVBSRkZEATJo0ic2bN7cZxNiyZQvXXutarjBx4kReffVVVFVl8+bNTJo0Cb1eT0REBFFR\nUeTk5KDT6bBardhsNjQaDQ6Hg5UrV/Lb3/62Oy6hT8jZvJOCegfj08LRGY3oAgLQ6Fwpc1itoKoo\nGgWN3gdrTTXbn3gca3WV+/WGmFhChw0j5sKLcTRbsDc2Ym9spGrHDkrWrkFVFHyuuIlqrZH1dX7s\nz66D4JkER2q4bNsbFH2+kqjzp+FrDjvja7A3NVG+aSN+4ZGEDB3qfjxv2YdU79pJU0kxDosFY3Iy\nA66/keC0QQBU7dpF6Xff0FiQz/6XXqSpqIi4uZeh0XftQ6/DaqV49Sp0gYGEDE3HLzy882Obm9H6\n+nbpvNaaGmy1tRhiY095bFPpUex1dYBCQ/4RAhISsNXWcvCN17FWVQLgFx5B3NzL0BoMGAckodH7\nkHe0nre/bjuAcfWUAVySEYcKfPBNLsOTTNx5ySA0GoXl3x9mXFo4AyIDAbjzElcf1jfZ+P1b29xV\nSManhfOTiwZiOMkARk/RaBQZwBBCCCGEEEKctm75NFNZWYnZfGxTP7PZzIEDBzo9RqvV4u/vT11d\nHZWVlQwcONB9nMlkorKykilTpvC3v/2NNWvWsGDBAlatWsX555+Pbxc/fPY31Q1WFq87ig0tlR+8\nSWRTGQA6oxGNTo+trhbV4UAXEEDMRZdQuz/bPYDhYzJhr6+nqaiQpqJCilavah9Aq+WHybezJ0cF\nbC3/c6mxOMkaNofzti/j8AfvM+iee8/oGpqrqtjzzF9pLMgHIOHqa4i58GLqDx2i4H+fuo8zjxvP\nwDvuYndhPZU7igk06AmZfS3jb7iRo19/Rd6yD8n/9GPyP/0Y3/BwUm/9CSHpw04a+8hHyyha9TkA\n+uBgxjz9F3QGA6qqYm9ooPirNTQcyaNyayYA4ZMmEz1jFhpfX3xNoe5lNKrTSfWe3TQVFVG+aSN1\nubmgqiQtuImYWRd1GNtpt1O0ehV5H7zXafuMScmk/uR2AuIT2jzucKq8uno/ThWmDY9i5uhYEiOM\nqC07bc7OiOPisbFojttHYkEnMyWMBj2/v3kM67YXk11Yw/wZKX1iAEMIIYQQQgghzlS/+UTj7+/P\nokWLAKivr+fjjz/moYce4qWXXqKhoYHLLruMtLS0Nq9Zs2YNa9asAeBPf/oTMTExnZ7/ZM/1hhhg\ntP8XbLSEsDbpYq4tXo22phx7fX2b4+wNDRxZvsz1b60Pk5/+C8EpAwn01VCSmcmu116luaYavdGI\nT4DR9f+BgeyMHc+ebWXu81x1/iCizQG8sNxVIWOXI5T40CT4cSNj77iLoJZ9GhxWK1ofn1O231JV\nxVcP/4bGoyXux44s+5Ajyz5sc1zizFmM+/VvKKlq5NnlG91VMQB+M38is+68m7hhw9n87BKsNTU0\nl5VxcOl/uPDFl9D5GbA3NtJYepQgwG6xYDCbaSwtpejLYwM3tpoafrz3bobedDP1RUUcWftVu/aW\n/fA9ZT983+ax9Ftvw1bfwP5lH7gf0+j1OG02Dr39FnFD04nKGAeA02Yj9/OVFH7/HRV79+BodpUW\n9Y+IwDckhKr9+4+d9+ZbGXLjfBStlhN9uG4feaX1RIT688sbJ2PwPfvZCqlJCac+qA/oa/egOD2S\nP+8geezfJH/9n+Swf5P8eQfJY9+nqOrxHxs9Y//+/XzwwQc88sgjgGujToArr7zSfcxTTz3Ftdde\nS1paGg6Hg7vuuot///vffPzxx22OPf64Vq+//joZGRkUFxej0+mYOHEiS5YsccfrTFFRUYePx8TE\ndPqcp2laNqnsSjkau8PJn9/fwYGiWgCC/PU8NCeZCKMera8vGh8fjn6znsaiIuosdv5Rl4pDde2P\nsGB6CmmxwVhsTgbGBreJl11Qw5/e346qwoNXDiPaZCAixACA1eZg9dZCPvzuML44uHz/R4Tp7cTO\nnkPF1kzqD+USkj4MQ2QksbPn4HvcjJvjry//85UcfvdtAhIHkP6rh6jI3ELh5ytprihHdTgwJqcw\n5P4H8AkJobiykcff3IrV7mpjakwQOS3XfNelgxiVbMag14CqsuOPT1Kfm9ulvo656GL8oqLJfeO1\nds/pjIEkXnMt1qoq6g/n4mi24mxupqm4CIfF0uH5QtKHMeT+hRSs/Iz8Tz8BIO6yy2kqLqZiy+Y2\nxxpiYkm4Yh5h4ycAUJ93mCMfLcM0ajSRF0zvsCJHbaOV3/xnMxargwevHMbIZNNp/b54Qk/Ha9UT\n96C392Vv5Q4kf/0xXke6M4/e3p/enD9v78tobm1HAAAUXklEQVS+kLtW3ZFDb+9PyZ9neXu8rvBk\nHnvy+rwld10dQOqWmRgpKSkUFxdTWlqKyWTihx9+YOHChW2OGTt2LOvWrSMtLY2NGzeSnp6Ooihk\nZGTw97//nblz51JVVUVxcTGpqcemyxcXF1NRUUF6ejp5eXn4+PigKApWq7U7LqVX6bQa7r1sCE+/\nt53Sagu1jTb+vb6QhVcMZfXmQqrrrUSbBnL5TTPZuK8Ux8psAOwOldfXHNtTYcGMVBSgptFKbYOV\nrNxKVBUuHRfPyOS2m6L66LVcOj6eQyV1ZOZUsDrxQq7KWU7eh++7j6netZPqXTupzNrG6D88jUav\np2zDDwSmpVG9fTuNhQWUtGwaGnn+NPSBgURdMJ2oC6bjtNuxVlbiExqKRq8nv6yexR/uxGp3oijw\n6I2jiAr154GXNmB3qLyyMpsgfz2/uno4iRFGhix8kD3P/JWGI65SobqAAPQGf1RFwVJW6m6jrzmM\nhCuvRuPrS1DqQGx1tRz5aBkN+UeImDyFhKuuRm8MbNfnTrudI8s/ombfXvSBRhzNVoLTBhF32eUo\nWi1arZbYiy5xD2IUrDi2LEZr8Cf5ppsJGTa83aaqxsQBDH3wVyfN94a9pVisDoYNCG2XFyGEEEII\nIYQQ3TSIodVquf3223nqqadwOp1Mnz6d+Ph43nvvPVJSUsjIyGDGjBk8//zz3H///RiNRn7xi18A\nEB8fz3nnnccvf/lLNBoNP/3pT90jPQDvvPMON954IwCTJ09m8eLFfPzxx1x33XXdcSm9LtToyx9v\ny+BoVRPPLt9FXmk9vzqu2gRAakwg+wtqXP+ODmLaiCjeXneQpmYHAG+dUOXC9Zogrpqc2GFMjaJw\n5+zBFLyZydHqEIoDoglSLdRNvYIy/EmuO0zw9ytorqggf8UnaPQ+5H+yvMNzBcTFYXc40WldOdTo\ndPhFRFDfZONQYSUvfbaPBoud9IQQ7pw9iBCja4+TX145jMycCrJyK6iobebxN7eiKDAoLpjr7vgF\nhs/ew2mzMeiee4lLTKSoqAh7YwPFa9agDw4idMRIKiwqQRonAfHxAIQMTT9lf2t0OgZc2/HvUlFF\nI9/uPkpVXTMXzL0SW84+gloG2LQGf0yjx+AfHe0+vrS6iaZmBwEGHc02B6FG306rguQdreedda4Z\nJucPizplO4UQQgghhBDiXNQty0n6qv62nORERRWNvP9NLnvzq2m2HXu9ouDeS+J380eREh2E06lS\nb7Hx7vpDNFsdBPrrCQ7QExzgQ2iAL8MGhKLXaTqJ5PL+N7ms3FzQ6fPjSzYxqmo3qsPhfswvMhLz\nmLEUfL6SI4EJ5J13FdlF9ZgCfbnivASmDY/maFUTv3sj0718ZHSKmXvnDumwPTa7k1c+38fm/eXu\nxyJDDTw2fzQVtRYaLHYiIsKoqqxEo1GIDPEjwE/P2u1FvLEmB51WYdboWG6Yltzu3HaHk+LKJlZl\nFjB8QChDEkIINOjbLPVwOFW25pSzcV8ZmQeOtWFMqpmfzWnf5sq6ZjZll5FTXMuW49oMkBhh5LEF\no/l2VwkrN+fTaLETHuzH4PgQth2soKSqibiwAB6bPwofvWu/DG+ZGnYqshyh/8U7nuSv/8XriCwn\n6T/xOiLLSfpHvJOR5Qh9P97JSP76fryukOUkvRuvq8tJzqlBjJKSkg4fj4qK6vQ5T/NEwu0OJxar\nA0WB55bvIrtlFsaIJBO/unp4mw/hZxMv62AFz3y00/3z2NQwNBraDCjMzf0fUY0lVI2fTfqwAVRF\npFDVaKcmaysrKoPandMU6IvD4aSm0VUNJTkqkEfnj3bP1OiI06my5UAZpkBf/v1FNkUVjZ0eGxLg\nw7xJA3h9zf42m4SOTQ3jzksHo9MqbNlfzhdb8skva8DhbPvr76PX4HComAN9mTsxgbIaCys2HnE/\nPygu2N3f49LCuXRcPIUVDazfUUxtk43SqiZaz6gAUSZ/LFY7VfVW9/mtto5zEeSvZ/GdEzD4HJut\n4S1vSKfSE/egt/dlb/4hIPnrf/E60p159Pb+9Ob8eXtf9oXcteqOHHp7f0r+PMvb43WFJ/Mogxin\nLyqqazPSvX4QY8uWLWRmZnL33Xd7zSDGicpqmsgpqnVtgHnCcoWziWd3OHn9y/3sPFxFXFgAv7hy\nGBpFYcPeo2zYW8qOQ5WEO+sZHWJjdW1oh+eYPDSSm2amsm5HMZ/8kIfF5pq1ER7sxxXnJTJ2YBgB\nfl2vwFFeY+G55Ts5UtYAQLC/nvjIYJosVg4W17Y59spJA2i2OVi52VXiNSzYD4vVTn2Tvd15A/x0\nqCo0Nrd/rtWs0THcdtFgtuaU88yyHR0eo9UojEkNIyU6kLEDw4gM9Qfgiy35vP31QcA1kHPDtGRQ\nFL7eXsSguGCCDD4MTQwhxhzQ5nze8oZ0KvIhuP/FO57kr//F64gMYvSfeB2RQYz+Ee9k5ENw3493\nMpK/vh+vK2QQo3fjdXUQo9+UWD1TGRkZZGRkACfv5J6+eTwZzxzoi3lQ+EnPeybxNAr85KK0Ex5V\nOW9IBGNSzSxauoWyOlh93NiBOciXpmaHezBg3KAwDD5aZmfEcdGYWCpqLZTXWEiIMGI06E+7baZA\nHx65cRQffnsIu1Pl5hmpxMXFUlRURFVdM++uz6WgvIHhA0xcPjEeh1MlIsSPNdsKKSg/NoNjRJKJ\nn80ZjMXmQKfREOjvaktpdRNPvp1FXZONqFBXxZYhCSHcMjMVRVFwOp2MTAplUFww+wtriAsLoL7J\nRlW9lRkjo7l2alKbgaTWa7twdAzRJgONFjujUsz4tiwXGZ8W1ub6PJm/s9Eb/zHpqZje3pe99YeA\n5K9/xuvp+N7en96cP2/vy97OXavuaoe396fkT+J5kqfb05PXd67kzusHMUT38NVruf78JP752T4U\nXEsrJqdHMjzJxO68KpYscy1DSQw3ul+j1ShEhBwr53o2sRfMSG33eGigLz+bO6TNYzqtwgUjopk0\nNJIVPx6hqKKRyybEMyDSVZnkxJkrESEGltw5Ho1G6XSJi6Io/OqqYagtbekKRVEYPkAqjgghhBBC\nCCHE2ZBBDHHGxg8KR1EUwoJ8SY527X+h0WgYPsBEekIIOp2GEKNPL7fSxUen4erJA7p2bBcGJrpy\njBBCCCGEEEIIz5JBDHHGFEVhfMsyluNpNAoPXTuiF1okhBBCCCGEEMKbnbzGphBCCCGEEEIIIUQf\ncU7NxGjdRfV0n+upNki8vh/X2/uzt/LXE7G9vS97M3c9Ed/b+7O389equ9rh7f3pzfnz9r7sK7lr\n5en2eHt/Sv48y9vjdZWn2tWT13eu5a5v/uZ40JYtW3j55Zd7uxlCCCGEEEIIIYQ4S14/E+NcKLEq\n8SRef4/XkzG9vS+lxKrE68vxvb0/vTl/3t6XvZ27VlKis3/E64zkr3/EOxUpsdp347Xy+pkYQggh\nhBBCCCGE8A4yiCGEEEIIIYQQQoh+QQYxhBBCCCGEEEII0S8oqqqqvd0IIYQQQgghhBBCiFORmRjA\nww8/3KPxerpairfHk/z173jQczn09r7srUpMkr/+Ge9E3Z1Hb+9Pb86ft/dlb+euVXfl0Nv7U/In\n8TzJ03nsyes7l3Ingxi9YOzYsRKvH/P2/vTm/Hl7X3pz7sD7+1PyJ/H6Km/vS2/OHXh/f0r+JF5f\n1pPXdy7lTgYxekFryVeJ1z95e396c/68vS+9OXfg/f0p+ZN4fZW396U35w68vz8lfxKvL+vJ6zuX\ncqd94oknnui16H1IcnJybzdBnAXJX/8nOezfJH/eQfLYv0n++j/JYf8m+fMOkse+Tzb2FEIIIYQQ\nQgghRL8gy0mEEEIIIYQQQgjRL+h6uwFnory8nBdeeIHq6moURWHWrFlceuml1NfX8+yzz1JWVkZ4\neDgPPvggRqORwsJCXnzxRQ4dOsQNN9zA5ZdfDoDVauXxxx/HbrfjcDiYOHEi1113XYcxn3rqKQ4c\nOMDgwYPb7Fr7xRdf8Nlnn3H06FH+/e9/ExQU1CN90J95Kn+tnE4nDz/8MCaTqdMdhdetW8dHH30E\nwFVXXcUFF1wAwBNPPEFVVRU+Pj4APProowQHB3ffxXuJ3sih3IOe48n83Xffffj5+aHRaNBqtfzp\nT3/qMGZWVhZLly7F6XQyc+ZM5s2bB8ALL7zAnj178Pf3d59vwIAB3d4H/V1v5PDFF19k69atBAcH\ns2TJEvfjGzZs4IMPPqCwsJA//vGPpKSkdPv1ewNP5rChoYGXXnqJ/Px8FEXhZz/7GWlpae1iyn3o\nWb2RQ7kPPcdT+SsqKuLZZ591n7e0tJTrrruOOXPmtIsp96Bn9UYO5R7sI9R+qLKyUj148KCqqqra\n2NioLly4UM3Pz1fffPNNdfny5aqqqury5cvVN998U1VVVa2urlYPHDigvv322+onn3ziPo/T6VSb\nmppUVVVVm82mLlq0SM3Ozu4w5o4dO9TNmzerTz/9dJvHc3Nz1aNHj6r33nuvWlNT4/Fr9Uaeyl+r\nFStWqM8991y73LSqq6tT77vvPrWurq7Nv1VVVR9//HE1JyenOy7Tq/V0DlVV7kFP8mT+utLvDodD\n/fnPf66WlJSoNptN/fWvf63m5+erqqqqzz//vLphwwZPX6LX6+kcqqqq7t69Wz148KD6y1/+ss3j\n+fn5amFhobyfniZP5vAf//iHumbNGlVVXX/P1NfXt4sn96Hn9XQOVVXuQ0/y9N8yquq6z+644w61\ntLS0w+fkHvSsns6hqso92Ff0y+UkoaGh7g1XDAYDsbGxVFZWsnnzZqZNmwbAtGnT2Lx5MwDBwcGk\npqai1WrbnEdRFPz8/ABwOBw4HA4URekw5vDhwzEYDO0eT0pKIiIiwmPXdi7wVP4AKioq2Lp1KzNn\nzuw0XlZWFiNGjMBoNGI0GhkxYgRZWVndcGXnjp7OIcg96EmezF9X5OTkEBUVRWRkJDqdjkmTJrnP\nLc5MT+cQYOjQoRiNxnaPx8XFERMTc8bnPVd5KoeNjY3s3buXGTNmAKDT6QgICGgXT+5Dz+vpHILc\nh57UHe+jO3fuJCoqivDw8HbPyT3oeT2dQ5B7sK/ol8tJjldaWsqhQ4dITU2lpqaG0NBQAEJCQqip\nqTnl651OJ7/97W8pKSnh4osvZuDAgd3dZHGcs83fa6+9xk033URTU1Onx1RWVmI2m90/m0wmKisr\n3T+/+OKLaDQaJkyYwNVXX93pQJboWE/kUHSfs80fuJb6AFx44YXMmjWr3fMn3oNms5kDBw64f37n\nnXf48MMPGTZsGAsWLECv15/NJZ1zeiKHonudTQ5LS0sJCgrixRdfJC8vj+TkZG677Tb3lzSt5D7s\nXj2RQ9F9PPE+CvD9998zefLkDp+Te7B79UQORd/RrwcxLBYLS5Ys4bbbbnOvIWulKEqXPoxqNBoW\nL15MQ0MDf/3rXzly5AgJCQnd1WRxnLPNX2ZmJsHBwSQnJ7N79+4zasPChQsxmUw0NTWxZMkSvvnm\nG/fIrTi1vpBDceY88R765JNPYjKZqKmp4Q9/+AMxMTEMHTq0y22YP38+ISEh2O12Xn75ZT755BOu\nueaa076Wc1VfyKE4O2ebQ4fDwaFDh7j99tsZOHAgS5cu5eOPP+aGG27ochvkPjw7fSGH4sx54n0U\nwG63k5mZyfz580+7DXIPnp2+kEPRs/rtIIbdbmfJkiVMnTqVCRMmAK4pQlVVVYSGhlJVVXVaG/wF\nBASQnp5OVlYWzc3NvPLKKwBcf/31ZGRkdMs1nMs8kb/s7Gy2bNnCtm3bsFqtNDU18fe//53Zs2e3\nyZ/JZGLPnj3u11VWVrr/QDeZTIBrCtqUKVPIycmRQYwu6skcyj3oeZ56D229h4KDgxk3bhw5OTlE\nRETw5z//GXB9sz9gwAAqKircr6moqHC/rvWbEr1ez/Tp01mxYoVHr9Ob9WQOL7roou67kHOYJ3Jo\nNpsxm83umaQTJ07k448/pry8XO7DHtCTOZT70PM8+Xli27ZtJCUlERISAiD3YA/pyRzKPdh39MtB\nDFVVeemll4iNjWXu3LnuxzMyMli/fj3z5s1j/fr1jBs37qTnqa2tRavVEhAQgNVqZceOHVxxxRUM\nHDiQxYsXd/dlnLM8lb/58+e7R0p3797NihUrWLhwIUCb/NXX1/POO+9QX18PwPbt25k/fz4Oh4OG\nhgaCgoLcI6/Dhw/39OV6pZ7OofAsT+XPYrGgqioGgwGLxcKOHTu45pprCAsLa5M/h8NBcXExpaWl\nmEwmfvjhB3eeW//IUFWVzZs3Ex8f3z0X7WV6OofC8zyVw5CQEMxmM0VFRcTExLBz507i4uLkPuwB\nPZ1D4Vmeyl+rE5chyD3Y/Xo6h6LvUFRVVXu7Eadr3759PPbYYyQkJLinB914440MHDiQZ599lvLy\n8jbldKqrq3n44Ydpampyb+b5zDPPUFZWxgsvvIDT6URVVc4777xOp2499thjFBYWYrFYCAwM5J57\n7mHUqFGsXLmSTz/9lOrqaoKDgxk9ejT33HNPT3ZHv+Op/B0/Xaz1A3Bn5TnXrl3L8uXLAVeJ1enT\np2OxWHj88cdxOBw4nU6GDx/OrbfeikbTL/e77VG9kUO5Bz3HU/mrq6vjr3/9K+D642zKlClcddVV\nHcbcunUrr7/+Ok6nk+nTp7uP+/3vf09tbS0AiYmJ3HXXXbIOvAt6I4fPPfcce/bsoa6ujuDgYK67\n7jpmzJjBpk2bePXVV6mtrSUgIIABAwbwyCOP9Fhf9FeefB89fPgwL730Ena7nYiICO69994ON577\n/+3bsQnAMAxEUc+reTysyrSBtAL7yHsriGu+sR3OOnFDO5wzeb/uXlW19t6f7wxvNjjrxA1t8A6R\nEQMAAAD4H0/OAAAAQAQRAwAAAIggYgAAAAARRAwAAAAggogBAAAARBAxAAAAgAgiBgAAABBBxAAA\nAAAiPI7x2yyINGmpAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f247869a9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'sys_analyser': {'benchmark_portfolio':              cash  market_value  static_unit_net_value  total_value  \\\n",
       "  date                                                                  \n",
       "  2014-01-03  745.3    9999254.70                  1.000  10000000.00   \n",
       "  2014-01-06  745.3    9771663.60                  1.000   9772408.90   \n",
       "  2014-01-07  745.3    9768870.00                  0.977   9769615.30   \n",
       "  2014-01-08  745.3    9785937.15                  0.977   9786682.45   \n",
       "  2014-01-09  745.3    9699990.30                  0.979   9700735.60   \n",
       "  2014-01-10  745.3    9624170.25                  0.970   9624915.55   \n",
       "  2014-01-13  745.3    9575413.20                  0.962   9576158.50   \n",
       "  2014-01-14  745.3    9659090.25                  0.958   9659835.55   \n",
       "  2014-01-15  745.3    9642023.10                  0.966   9642768.40   \n",
       "  2014-01-16  745.3    9654681.60                  0.964   9655426.90   \n",
       "  2014-01-17  745.3    9509108.85                  0.966   9509854.15   \n",
       "  2014-01-20  745.3    9454546.35                  0.951   9455291.65   \n",
       "  2014-01-21  745.3    9548044.65                  0.946   9548789.95   \n",
       "  2014-01-22  745.3    9794187.00                  0.955   9794932.30   \n",
       "  2014-01-23  745.3    9742199.85                  0.979   9742945.15   \n",
       "  2014-01-24  745.3    9802393.20                  0.974   9803138.50   \n",
       "  2014-01-27  745.3    9672490.80                  0.980   9673236.10   \n",
       "  2014-01-28  745.3    9689688.90                  0.967   9690434.20   \n",
       "  2014-01-29  745.3    9724259.70                  0.969   9725005.00   \n",
       "  2014-01-30  745.3    9613694.25                  0.973   9614439.55   \n",
       "  2014-02-07  745.3    9657475.20                  0.961   9658220.50   \n",
       "  2014-02-10  745.3    9897768.45                  0.966   9898513.75   \n",
       "  2014-02-11  745.3    9976469.40                  0.990   9977214.70   \n",
       "  2014-02-12  745.3   10001306.25                  0.998  10002051.55   \n",
       "  2014-02-13  745.3    9950235.75                  1.000   9950981.05   \n",
       "  2014-02-14  745.3   10020206.70                  0.995  10020952.00   \n",
       "  2014-02-17  745.3   10090352.25                  1.002  10091097.55   \n",
       "  2014-02-18  745.3    9962850.60                  1.009   9963595.90   \n",
       "  2014-02-19  745.3   10077300.90                  0.996  10078046.20   \n",
       "  2014-02-20  745.3    9984675.60                  1.008   9985420.90   \n",
       "  ...           ...           ...                    ...          ...   \n",
       "  2017-12-11  745.3   17763367.50                  1.748  17764112.80   \n",
       "  2017-12-12  745.3   17529927.30                  1.776  17530672.60   \n",
       "  2017-12-13  745.3   17678642.85                  1.753  17679388.15   \n",
       "  2017-12-14  745.3   17574144.75                  1.768  17574890.05   \n",
       "  2017-12-15  745.3   17376453.90                  1.757  17377199.20   \n",
       "  2017-12-18  745.3   17395790.85                  1.738  17396536.15   \n",
       "  2017-12-19  745.3   17614215.45                  1.740  17614960.75   \n",
       "  2017-12-20  745.3   17593088.85                  1.761  17593834.15   \n",
       "  2017-12-21  745.3   17756165.25                  1.759  17756910.55   \n",
       "  2017-12-22  745.3   17698329.00                  1.776  17699074.30   \n",
       "  2017-12-25  745.3   17641322.10                  1.770  17642067.40   \n",
       "  2017-12-26  745.3   17694051.30                  1.764  17694796.60   \n",
       "  2017-12-27  745.3   17421631.65                  1.769  17422376.95   \n",
       "  2017-12-28  745.3   17542498.50                  1.742  17543243.80   \n",
       "  2017-12-29  745.3   17594660.25                  1.754  17595405.55   \n",
       "  2018-01-02  745.3   17841501.00                  1.760  17842246.30   \n",
       "  2018-01-03  745.3   17946217.35                  1.784  17946962.65   \n",
       "  2018-01-04  745.3   18022255.65                  1.795  18023000.95   \n",
       "  2018-01-05  745.3   18065643.75                  1.802  18066389.05   \n",
       "  2018-01-08  745.3   18159098.40                  1.807  18159843.70   \n",
       "  2018-01-09  745.3   18286294.50                  1.816  18287039.80   \n",
       "  2018-01-10  745.3   18367090.65                  1.829  18367835.95   \n",
       "  2018-01-11  745.3   18357400.35                  1.837  18358145.65   \n",
       "  2018-01-12  745.3   18442125.00                  1.836  18442870.30   \n",
       "  2018-01-15  745.3   18443172.60                  1.844  18443917.90   \n",
       "  2018-01-16  745.3   18588221.55                  1.844  18588966.85   \n",
       "  2018-01-17  745.3   18543043.80                  1.859  18543789.10   \n",
       "  2018-01-18  745.3   18644748.30                  1.854  18645493.60   \n",
       "  2018-01-19  745.3   18705771.00                  1.865  18706516.30   \n",
       "  2018-01-22  745.3   18929259.00                  1.871  18930004.30   \n",
       "  \n",
       "              unit_net_value       units  \n",
       "  date                                    \n",
       "  2014-01-03        1.000000  10000000.0  \n",
       "  2014-01-06        0.977241  10000000.0  \n",
       "  2014-01-07        0.976962  10000000.0  \n",
       "  2014-01-08        0.978668  10000000.0  \n",
       "  2014-01-09        0.970074  10000000.0  \n",
       "  2014-01-10        0.962492  10000000.0  \n",
       "  2014-01-13        0.957616  10000000.0  \n",
       "  2014-01-14        0.965984  10000000.0  \n",
       "  2014-01-15        0.964277  10000000.0  \n",
       "  2014-01-16        0.965543  10000000.0  \n",
       "  2014-01-17        0.950985  10000000.0  \n",
       "  2014-01-20        0.945529  10000000.0  \n",
       "  2014-01-21        0.954879  10000000.0  \n",
       "  2014-01-22        0.979493  10000000.0  \n",
       "  2014-01-23        0.974295  10000000.0  \n",
       "  2014-01-24        0.980314  10000000.0  \n",
       "  2014-01-27        0.967324  10000000.0  \n",
       "  2014-01-28        0.969043  10000000.0  \n",
       "  2014-01-29        0.972500  10000000.0  \n",
       "  2014-01-30        0.961444  10000000.0  \n",
       "  2014-02-07        0.965822  10000000.0  \n",
       "  2014-02-10        0.989851  10000000.0  \n",
       "  2014-02-11        0.997721  10000000.0  \n",
       "  2014-02-12        1.000205  10000000.0  \n",
       "  2014-02-13        0.995098  10000000.0  \n",
       "  2014-02-14        1.002095  10000000.0  \n",
       "  2014-02-17        1.009110  10000000.0  \n",
       "  2014-02-18        0.996360  10000000.0  \n",
       "  2014-02-19        1.007805  10000000.0  \n",
       "  2014-02-20        0.998542  10000000.0  \n",
       "  ...                    ...         ...  \n",
       "  2017-12-11        1.776411  10000000.0  \n",
       "  2017-12-12        1.753067  10000000.0  \n",
       "  2017-12-13        1.767939  10000000.0  \n",
       "  2017-12-14        1.757489  10000000.0  \n",
       "  2017-12-15        1.737720  10000000.0  \n",
       "  2017-12-18        1.739654  10000000.0  \n",
       "  2017-12-19        1.761496  10000000.0  \n",
       "  2017-12-20        1.759383  10000000.0  \n",
       "  2017-12-21        1.775691  10000000.0  \n",
       "  2017-12-22        1.769907  10000000.0  \n",
       "  2017-12-25        1.764207  10000000.0  \n",
       "  2017-12-26        1.769480  10000000.0  \n",
       "  2017-12-27        1.742238  10000000.0  \n",
       "  2017-12-28        1.754324  10000000.0  \n",
       "  2017-12-29        1.759541  10000000.0  \n",
       "  2018-01-02        1.784225  10000000.0  \n",
       "  2018-01-03        1.794696  10000000.0  \n",
       "  2018-01-04        1.802300  10000000.0  \n",
       "  2018-01-05        1.806639  10000000.0  \n",
       "  2018-01-08        1.815984  10000000.0  \n",
       "  2018-01-09        1.828704  10000000.0  \n",
       "  2018-01-10        1.836784  10000000.0  \n",
       "  2018-01-11        1.835815  10000000.0  \n",
       "  2018-01-12        1.844287  10000000.0  \n",
       "  2018-01-15        1.844392  10000000.0  \n",
       "  2018-01-16        1.858897  10000000.0  \n",
       "  2018-01-17        1.854379  10000000.0  \n",
       "  2018-01-18        1.864549  10000000.0  \n",
       "  2018-01-19        1.870652  10000000.0  \n",
       "  2018-01-22        1.893000  10000000.0  \n",
       "  \n",
       "  [991 rows x 6 columns],\n",
       "  'portfolio':                    cash  market_value  static_unit_net_value   total_value  \\\n",
       "  date                                                                         \n",
       "  2014-01-03  9736148.000  2.634470e+05                  1.000  9.999595e+06   \n",
       "  2014-01-06  9429722.000  5.606790e+05                  1.000  9.990401e+06   \n",
       "  2014-01-07  9125957.000  8.627950e+05                  0.999  9.988752e+06   \n",
       "  2014-01-08  8829838.000  1.151396e+06                  0.999  9.981234e+06   \n",
       "  2014-01-09  8517260.115  1.455680e+06                  0.998  9.972940e+06   \n",
       "  2014-01-10  8220735.115  1.743951e+06                  0.997  9.964686e+06   \n",
       "  2014-01-13  7923490.365  2.039548e+06                  0.996  9.963038e+06   \n",
       "  2014-01-14  7641301.300  2.343817e+06                  0.996  9.985118e+06   \n",
       "  2014-01-15  7330628.300  2.639467e+06                  0.999  9.970095e+06   \n",
       "  2014-01-16  7032966.937  2.950442e+06                  0.997  9.983409e+06   \n",
       "  2014-01-17  6701326.937  3.223152e+06                  0.998  9.924479e+06   \n",
       "  2014-01-20  6392989.937  3.517394e+06                  0.992  9.910384e+06   \n",
       "  2014-01-21  6125060.032  3.827056e+06                  0.991  9.952116e+06   \n",
       "  2014-01-22  5891885.985  4.181776e+06                  0.995  1.007366e+07   \n",
       "  2014-01-23  5578078.794  4.481338e+06                  1.007  1.005942e+07   \n",
       "  2014-01-24  5302402.509  4.806678e+06                  1.006  1.010908e+07   \n",
       "  2014-01-27  4987108.889  5.071589e+06                  1.011  1.005870e+07   \n",
       "  2014-01-28  4674981.482  5.375022e+06                  1.006  1.005000e+07   \n",
       "  2014-01-29  4372944.127  5.666191e+06                  1.005  1.003914e+07   \n",
       "  2014-01-30  4059848.347  5.919470e+06                  1.004  9.979318e+06   \n",
       "  2014-02-07  3764969.786  6.244223e+06                  0.998  1.000919e+07   \n",
       "  2014-02-10  3508528.254  6.663334e+06                  1.001  1.017186e+07   \n",
       "  2014-02-11  3244896.982  7.016827e+06                  1.017  1.026172e+07   \n",
       "  2014-02-12  2923763.465  7.345821e+06                  1.026  1.027194e+07   \n",
       "  2014-02-13  2609147.701  7.608109e+06                  1.027  1.021962e+07   \n",
       "  2014-02-14  2317513.517  7.969231e+06                  1.022  1.028910e+07   \n",
       "  2014-02-17  2022021.288  8.339898e+06                  1.029  1.036428e+07   \n",
       "  2014-02-18  1695707.142  8.576605e+06                  1.036  1.027231e+07   \n",
       "  2014-02-19  1408575.903  8.964262e+06                  1.027  1.037284e+07   \n",
       "  2014-02-20  1097046.091  9.262863e+06                  1.037  1.035991e+07   \n",
       "  ...                 ...           ...                    ...           ...   \n",
       "  2017-12-11  2080687.653  1.967799e+07                  2.157  2.175868e+07   \n",
       "  2017-12-12  2080687.653  1.944608e+07                  2.176  2.152677e+07   \n",
       "  2017-12-13  2080687.653  1.956060e+07                  2.153  2.164129e+07   \n",
       "  2017-12-14  2080687.653  1.945345e+07                  2.164  2.153414e+07   \n",
       "  2017-12-15  2080687.653  1.927484e+07                  2.153  2.135553e+07   \n",
       "  2017-12-18  2080687.653  1.930513e+07                  2.136  2.138582e+07   \n",
       "  2017-12-19  2080687.653  1.948858e+07                  2.139  2.156927e+07   \n",
       "  2017-12-20  2080687.653  1.942397e+07                  2.157  2.150466e+07   \n",
       "  2017-12-21  2080687.653  1.952713e+07                  2.150  2.160782e+07   \n",
       "  2017-12-22  2080687.653  1.948046e+07                  2.161  2.156114e+07   \n",
       "  2017-12-25  2080687.653  1.948894e+07                  2.156  2.156963e+07   \n",
       "  2017-12-26  2080687.653  1.963876e+07                  2.157  2.171945e+07   \n",
       "  2017-12-27  2080687.653  1.945133e+07                  2.172  2.153202e+07   \n",
       "  2017-12-28  2080687.653  1.949236e+07                  2.153  2.157305e+07   \n",
       "  2017-12-29  2080687.653  1.961124e+07                  2.157  2.169192e+07   \n",
       "  2018-01-02  2080687.653  1.997070e+07                  2.169  2.205139e+07   \n",
       "  2018-01-03  2080687.653  2.009503e+07                  2.205  2.217572e+07   \n",
       "  2018-01-04  2080687.653  2.014488e+07                  2.218  2.222556e+07   \n",
       "  2018-01-05  2080687.653  2.030836e+07                  2.223  2.238904e+07   \n",
       "  2018-01-08  2080687.653  2.050520e+07                  2.239  2.258589e+07   \n",
       "  2018-01-09  2080687.653  2.049973e+07                  2.259  2.258042e+07   \n",
       "  2018-01-10  2080687.653  2.057219e+07                  2.258  2.265287e+07   \n",
       "  2018-01-11  2080687.653  2.051731e+07                  2.265  2.259800e+07   \n",
       "  2018-01-12  2080687.653  2.057443e+07                  2.260  2.265512e+07   \n",
       "  2018-01-15  2080687.653  2.057292e+07                  2.266  2.265361e+07   \n",
       "  2018-01-16  2080687.653  2.087998e+07                  2.265  2.296067e+07   \n",
       "  2018-01-17  2080687.653  2.087841e+07                  2.296  2.295910e+07   \n",
       "  2018-01-18  2080687.653  2.102167e+07                  2.296  2.310235e+07   \n",
       "  2018-01-19  2080687.653  2.104398e+07                  2.310  2.312467e+07   \n",
       "  2018-01-22  2080687.653  2.114470e+07                  2.312  2.322539e+07   \n",
       "  \n",
       "              unit_net_value       units  \n",
       "  date                                    \n",
       "  2014-01-03        0.999960  10000000.0  \n",
       "  2014-01-06        0.999040  10000000.0  \n",
       "  2014-01-07        0.998875  10000000.0  \n",
       "  2014-01-08        0.998123  10000000.0  \n",
       "  2014-01-09        0.997294  10000000.0  \n",
       "  2014-01-10        0.996469  10000000.0  \n",
       "  2014-01-13        0.996304  10000000.0  \n",
       "  2014-01-14        0.998512  10000000.0  \n",
       "  2014-01-15        0.997010  10000000.0  \n",
       "  2014-01-16        0.998341  10000000.0  \n",
       "  2014-01-17        0.992448  10000000.0  \n",
       "  2014-01-20        0.991038  10000000.0  \n",
       "  2014-01-21        0.995212  10000000.0  \n",
       "  2014-01-22        1.007366  10000000.0  \n",
       "  2014-01-23        1.005942  10000000.0  \n",
       "  2014-01-24        1.010908  10000000.0  \n",
       "  2014-01-27        1.005870  10000000.0  \n",
       "  2014-01-28        1.005000  10000000.0  \n",
       "  2014-01-29        1.003914  10000000.0  \n",
       "  2014-01-30        0.997932  10000000.0  \n",
       "  2014-02-07        1.000919  10000000.0  \n",
       "  2014-02-10        1.017186  10000000.0  \n",
       "  2014-02-11        1.026172  10000000.0  \n",
       "  2014-02-12        1.027194  10000000.0  \n",
       "  2014-02-13        1.021962  10000000.0  \n",
       "  2014-02-14        1.028910  10000000.0  \n",
       "  2014-02-17        1.036428  10000000.0  \n",
       "  2014-02-18        1.027231  10000000.0  \n",
       "  2014-02-19        1.037284  10000000.0  \n",
       "  2014-02-20        1.035991  10000000.0  \n",
       "  ...                    ...         ...  \n",
       "  2017-12-11        2.175868  10000000.0  \n",
       "  2017-12-12        2.152677  10000000.0  \n",
       "  2017-12-13        2.164129  10000000.0  \n",
       "  2017-12-14        2.153414  10000000.0  \n",
       "  2017-12-15        2.135553  10000000.0  \n",
       "  2017-12-18        2.138582  10000000.0  \n",
       "  2017-12-19        2.156927  10000000.0  \n",
       "  2017-12-20        2.150466  10000000.0  \n",
       "  2017-12-21        2.160782  10000000.0  \n",
       "  2017-12-22        2.156114  10000000.0  \n",
       "  2017-12-25        2.156963  10000000.0  \n",
       "  2017-12-26        2.171945  10000000.0  \n",
       "  2017-12-27        2.153202  10000000.0  \n",
       "  2017-12-28        2.157305  10000000.0  \n",
       "  2017-12-29        2.169192  10000000.0  \n",
       "  2018-01-02        2.205139  10000000.0  \n",
       "  2018-01-03        2.217572  10000000.0  \n",
       "  2018-01-04        2.222556  10000000.0  \n",
       "  2018-01-05        2.238904  10000000.0  \n",
       "  2018-01-08        2.258589  10000000.0  \n",
       "  2018-01-09        2.258042  10000000.0  \n",
       "  2018-01-10        2.265287  10000000.0  \n",
       "  2018-01-11        2.259800  10000000.0  \n",
       "  2018-01-12        2.265512  10000000.0  \n",
       "  2018-01-15        2.265361  10000000.0  \n",
       "  2018-01-16        2.296067  10000000.0  \n",
       "  2018-01-17        2.295910  10000000.0  \n",
       "  2018-01-18        2.310235  10000000.0  \n",
       "  2018-01-19        2.312467  10000000.0  \n",
       "  2018-01-22        2.322539  10000000.0  \n",
       "  \n",
       "  [991 rows x 6 columns],\n",
       "  'stock_account':                    cash  dividend_receivable  market_value   total_value  \\\n",
       "  date                                                                       \n",
       "  2014-01-03  9736148.000                  0.0  2.634470e+05  9.999595e+06   \n",
       "  2014-01-06  9429722.000                  0.0  5.606790e+05  9.990401e+06   \n",
       "  2014-01-07  9125957.000                  0.0  8.627950e+05  9.988752e+06   \n",
       "  2014-01-08  8829838.000                  0.0  1.151396e+06  9.981234e+06   \n",
       "  2014-01-09  8517260.115                  0.0  1.455680e+06  9.972940e+06   \n",
       "  2014-01-10  8220735.115                  0.0  1.743951e+06  9.964686e+06   \n",
       "  2014-01-13  7923490.365                  0.0  2.039548e+06  9.963038e+06   \n",
       "  2014-01-14  7641301.300                  0.0  2.343817e+06  9.985118e+06   \n",
       "  2014-01-15  7330628.300                  0.0  2.639467e+06  9.970095e+06   \n",
       "  2014-01-16  7032966.937                  0.0  2.950442e+06  9.983409e+06   \n",
       "  2014-01-17  6701326.937                  0.0  3.223152e+06  9.924479e+06   \n",
       "  2014-01-20  6392989.937                  0.0  3.517394e+06  9.910384e+06   \n",
       "  2014-01-21  6125060.032                  0.0  3.827056e+06  9.952116e+06   \n",
       "  2014-01-22  5891885.985                  0.0  4.181776e+06  1.007366e+07   \n",
       "  2014-01-23  5578078.794                  0.0  4.481338e+06  1.005942e+07   \n",
       "  2014-01-24  5302402.509                  0.0  4.806678e+06  1.010908e+07   \n",
       "  2014-01-27  4987108.889                  0.0  5.071589e+06  1.005870e+07   \n",
       "  2014-01-28  4674981.482                  0.0  5.375022e+06  1.005000e+07   \n",
       "  2014-01-29  4372944.127                  0.0  5.666191e+06  1.003914e+07   \n",
       "  2014-01-30  4059848.347                  0.0  5.919470e+06  9.979318e+06   \n",
       "  2014-02-07  3764969.786                  0.0  6.244223e+06  1.000919e+07   \n",
       "  2014-02-10  3508528.254                  0.0  6.663334e+06  1.017186e+07   \n",
       "  2014-02-11  3244896.982                  0.0  7.016827e+06  1.026172e+07   \n",
       "  2014-02-12  2923763.465               2360.0  7.345821e+06  1.027194e+07   \n",
       "  2014-02-13  2609147.701               2360.0  7.608109e+06  1.021962e+07   \n",
       "  2014-02-14  2317513.517               2360.0  7.969231e+06  1.028910e+07   \n",
       "  2014-02-17  2022021.288               2360.0  8.339898e+06  1.036428e+07   \n",
       "  2014-02-18  1695707.142                  0.0  8.576605e+06  1.027231e+07   \n",
       "  2014-02-19  1408575.903                  0.0  8.964262e+06  1.037284e+07   \n",
       "  2014-02-20  1097046.091                  0.0  9.262863e+06  1.035991e+07   \n",
       "  ...                 ...                  ...           ...           ...   \n",
       "  2017-12-11  2080687.653                  0.0  1.967799e+07  2.175868e+07   \n",
       "  2017-12-12  2080687.653                  0.0  1.944608e+07  2.152677e+07   \n",
       "  2017-12-13  2080687.653                  0.0  1.956060e+07  2.164129e+07   \n",
       "  2017-12-14  2080687.653                  0.0  1.945345e+07  2.153414e+07   \n",
       "  2017-12-15  2080687.653                  0.0  1.927484e+07  2.135553e+07   \n",
       "  2017-12-18  2080687.653                  0.0  1.930513e+07  2.138582e+07   \n",
       "  2017-12-19  2080687.653                  0.0  1.948858e+07  2.156927e+07   \n",
       "  2017-12-20  2080687.653                  0.0  1.942397e+07  2.150466e+07   \n",
       "  2017-12-21  2080687.653                  0.0  1.952713e+07  2.160782e+07   \n",
       "  2017-12-22  2080687.653                  0.0  1.948046e+07  2.156114e+07   \n",
       "  2017-12-25  2080687.653                  0.0  1.948894e+07  2.156963e+07   \n",
       "  2017-12-26  2080687.653                  0.0  1.963876e+07  2.171945e+07   \n",
       "  2017-12-27  2080687.653                  0.0  1.945133e+07  2.153202e+07   \n",
       "  2017-12-28  2080687.653                  0.0  1.949236e+07  2.157305e+07   \n",
       "  2017-12-29  2080687.653                  0.0  1.961124e+07  2.169192e+07   \n",
       "  2018-01-02  2080687.653                  0.0  1.997070e+07  2.205139e+07   \n",
       "  2018-01-03  2080687.653                  0.0  2.009503e+07  2.217572e+07   \n",
       "  2018-01-04  2080687.653                  0.0  2.014488e+07  2.222556e+07   \n",
       "  2018-01-05  2080687.653                  0.0  2.030836e+07  2.238904e+07   \n",
       "  2018-01-08  2080687.653                  0.0  2.050520e+07  2.258589e+07   \n",
       "  2018-01-09  2080687.653                  0.0  2.049973e+07  2.258042e+07   \n",
       "  2018-01-10  2080687.653                  0.0  2.057219e+07  2.265287e+07   \n",
       "  2018-01-11  2080687.653                  0.0  2.051731e+07  2.259800e+07   \n",
       "  2018-01-12  2080687.653                  0.0  2.057443e+07  2.265512e+07   \n",
       "  2018-01-15  2080687.653                  0.0  2.057292e+07  2.265361e+07   \n",
       "  2018-01-16  2080687.653                  0.0  2.087998e+07  2.296067e+07   \n",
       "  2018-01-17  2080687.653                  0.0  2.087841e+07  2.295910e+07   \n",
       "  2018-01-18  2080687.653                  0.0  2.102167e+07  2.310235e+07   \n",
       "  2018-01-19  2080687.653                  0.0  2.104398e+07  2.312467e+07   \n",
       "  2018-01-22  2080687.653                  0.0  2.114470e+07  2.322539e+07   \n",
       "  \n",
       "              transaction_cost  \n",
       "  date                          \n",
       "  2014-01-03           405.000  \n",
       "  2014-01-06           415.000  \n",
       "  2014-01-07           410.000  \n",
       "  2014-01-08           425.000  \n",
       "  2014-01-09           440.885  \n",
       "  2014-01-10           455.000  \n",
       "  2014-01-13           441.750  \n",
       "  2014-01-14           446.065  \n",
       "  2014-01-15           450.000  \n",
       "  2014-01-16           435.363  \n",
       "  2014-01-17           450.000  \n",
       "  2014-01-20           440.000  \n",
       "  2014-01-21           437.905  \n",
       "  2014-01-22           462.047  \n",
       "  2014-01-23           433.191  \n",
       "  2014-01-24           441.285  \n",
       "  2014-01-27           431.620  \n",
       "  2014-01-28           420.407  \n",
       "  2014-01-29           423.355  \n",
       "  2014-01-30           459.780  \n",
       "  2014-02-07           458.561  \n",
       "  2014-02-10           508.532  \n",
       "  2014-02-11           516.272  \n",
       "  2014-02-12           495.516  \n",
       "  2014-02-13           551.764  \n",
       "  2014-02-14           539.184  \n",
       "  2014-02-17           515.229  \n",
       "  2014-02-18           523.146  \n",
       "  2014-02-19           538.239  \n",
       "  2014-02-20           553.812  \n",
       "  ...                      ...  \n",
       "  2017-12-11             0.000  \n",
       "  2017-12-12             0.000  \n",
       "  2017-12-13             0.000  \n",
       "  2017-12-14             0.000  \n",
       "  2017-12-15             0.000  \n",
       "  2017-12-18             0.000  \n",
       "  2017-12-19             0.000  \n",
       "  2017-12-20             0.000  \n",
       "  2017-12-21             0.000  \n",
       "  2017-12-22             0.000  \n",
       "  2017-12-25             0.000  \n",
       "  2017-12-26             0.000  \n",
       "  2017-12-27             0.000  \n",
       "  2017-12-28             0.000  \n",
       "  2017-12-29             0.000  \n",
       "  2018-01-02             0.000  \n",
       "  2018-01-03             0.000  \n",
       "  2018-01-04             0.000  \n",
       "  2018-01-05             0.000  \n",
       "  2018-01-08             0.000  \n",
       "  2018-01-09             0.000  \n",
       "  2018-01-10             0.000  \n",
       "  2018-01-11             0.000  \n",
       "  2018-01-12             0.000  \n",
       "  2018-01-15             0.000  \n",
       "  2018-01-16             0.000  \n",
       "  2018-01-17             0.000  \n",
       "  2018-01-18             0.000  \n",
       "  2018-01-19             0.000  \n",
       "  2018-01-22             0.000  \n",
       "  \n",
       "  [991 rows x 5 columns],\n",
       "  'stock_positions':             avg_price  last_price  market_value order_book_id  quantity symbol\n",
       "  date                                                                          \n",
       "  2014-01-03     11.930       11.93        3579.0   000001.XSHE     300.0   平安银行\n",
       "  2014-01-03      7.840        7.84        3136.0   000002.XSHE     400.0    万科A\n",
       "  2014-01-03     20.190       20.19        2019.0   000024.XSHE     100.0   招商地产\n",
       "  2014-01-03     14.070       14.07        2814.0   000063.XSHE     200.0   中兴通讯\n",
       "  2014-01-03      5.150        5.15        3605.0   000069.XSHE     700.0   华侨城A\n",
       "  2014-01-03      5.330        5.33        3198.0   000157.XSHE     600.0   中联重科\n",
       "  2014-01-03     18.330       18.33        3666.0   000338.XSHE     200.0   潍柴动力\n",
       "  2014-01-03      7.500        7.50        3000.0   000425.XSHE     400.0   徐工机械\n",
       "  2014-01-03      9.740        9.74        2922.0   000630.XSHE     300.0   铜陵有色\n",
       "  2014-01-03     30.990       30.99        3099.0   000651.XSHE     100.0   格力电器\n",
       "  2014-01-03      7.920        7.92        3168.0   000656.XSHE     400.0   金科股份\n",
       "  2014-01-03     12.100       12.10        3630.0   000776.XSHE     300.0   广发证券\n",
       "  2014-01-03      4.680        4.68        3276.0   000933.XSHE     700.0   神火股份\n",
       "  2014-01-03      7.150        7.15        3575.0   000937.XSHE     500.0   冀中能源\n",
       "  2014-01-03     10.500       10.50        3150.0   000960.XSHE     300.0   锡业股份\n",
       "  2014-01-03      6.920        6.92        3460.0   000961.XSHE     500.0   中南建设\n",
       "  2014-01-03      6.820        6.82        3410.0   000983.XSHE     500.0   西山煤电\n",
       "  2014-01-03     19.060       19.06        1906.0   002001.XSHE     100.0    新和成\n",
       "  2014-01-03      9.640        9.64        2892.0   002299.XSHE     300.0   圣农发展\n",
       "  2014-01-03     24.600       24.60        2460.0   002375.XSHE     100.0   亚厦股份\n",
       "  2014-01-03      9.140        9.14        3656.0   600000.XSHG     400.0   浦发银行\n",
       "  2014-01-03      4.980        4.98        3486.0   600011.XSHG     700.0   华能国际\n",
       "  2014-01-03      7.610        7.61        3044.0   600016.XSHG     400.0   民生银行\n",
       "  2014-01-03      4.010        4.01        3609.0   600019.XSHG     900.0   宝钢股份\n",
       "  2014-01-03      2.990        2.99        3588.0   600027.XSHG    1200.0   华电国际\n",
       "  2014-01-03      4.380        4.38        3504.0   600028.XSHG     800.0   中国石化\n",
       "  2014-01-03      2.700        2.70        3510.0   600029.XSHG    1300.0   南方航空\n",
       "  2014-01-03      8.110        8.11        3244.0   600048.XSHG     400.0   保利地产\n",
       "  2014-01-03     17.650       17.65        3530.0   600066.XSHG     200.0   宇通客车\n",
       "  2014-01-03      3.940        3.94        3546.0   600068.XSHG     900.0    葛洲坝\n",
       "  ...               ...         ...           ...           ...       ...    ...\n",
       "  2018-01-22     18.690       19.79       57391.0   600362.XSHG    2900.0   江西铜业\n",
       "  2018-01-22      7.375        6.88      129344.0   601919.XSHG   18800.0   中远海控\n",
       "  2018-01-22     58.643       60.74      218664.0   601336.XSHG    3600.0   新华保险\n",
       "  2018-01-22      7.653        6.64       14608.0   601727.XSHG    2200.0   上海电气\n",
       "  2018-01-22     21.661       20.59       78242.0   601688.XSHG    3800.0   华泰证券\n",
       "  2018-01-22      6.402        6.65      202825.0   600688.XSHG   30500.0   上海石化\n",
       "  2018-01-22     18.511       18.22       34618.0   600739.XSHG    1900.0   辽宁成大\n",
       "  2018-01-22      5.875        5.06       23782.0   600369.XSHG    4700.0   西南证券\n",
       "  2018-01-22     13.940       13.40        8040.0   002736.XSHE     600.0   国信证券\n",
       "  2018-01-22     17.568       21.20       19080.0   600030.XSHG     900.0   中信证券\n",
       "  2018-01-22     15.532       14.59       23344.0   601788.XSHG    1600.0   光大证券\n",
       "  2018-01-22      6.455        5.98       25714.0   601118.XSHG    4300.0   海南橡胶\n",
       "  2018-01-22      3.720        3.36       25536.0   600157.XSHG    7600.0   永泰能源\n",
       "  2018-01-22      5.982        5.38       48420.0   601018.XSHG    9000.0    宁波港\n",
       "  2018-01-22      3.413        3.21      149265.0   600795.XSHG   46500.0   国电电力\n",
       "  2018-01-22      7.766        8.09       33978.0   601600.XSHG    4200.0   中国铝业\n",
       "  2018-01-22      7.296        6.17       15425.0   000959.XSHE    2500.0   首钢股份\n",
       "  2018-01-22     19.104       18.89       24557.0   000776.XSHE    1300.0   广发证券\n",
       "  2018-01-22     11.978       13.84       53976.0   002024.XSHE    3900.0   苏宁云商\n",
       "  2018-01-22      9.861       12.06       20502.0   601766.XSHG    1700.0   中国中车\n",
       "  2018-01-22     10.324       12.89       41248.0   600352.XSHG    3200.0   浙江龙盛\n",
       "  2018-01-22      8.500        9.35        8415.0   601225.XSHG     900.0   陕西煤业\n",
       "  2018-01-22     27.897       30.94       64974.0   601628.XSHG    2100.0   中国人寿\n",
       "  2018-01-22     15.446       14.63       16093.0   002299.XSHE    1100.0   圣农发展\n",
       "  2018-01-22      7.346        6.85       71925.0   600050.XSHG   10500.0   中国联通\n",
       "  2018-01-22      8.600        6.42        6420.0   601718.XSHG    1000.0   际华集团\n",
       "  2018-01-22     12.398       10.19       49931.0   600100.XSHG    4900.0   同方股份\n",
       "  2018-01-22     22.260       23.31        6993.0   000623.XSHE     300.0   吉林敖东\n",
       "  2018-01-22     14.789       13.97       32131.0   600837.XSHG    2300.0   海通证券\n",
       "  2018-01-22     31.334       32.19       16095.0   600547.XSHG     500.0   山东黄金\n",
       "  \n",
       "  [159399 rows x 6 columns],\n",
       "  'summary': {'STOCK': 10000000.0,\n",
       "   'alpha': 0.060999999999999999,\n",
       "   'annualized_returns': 0.23100000000000001,\n",
       "   'benchmark': '000300.XSHG',\n",
       "   'benchmark_annualized_returns': 0.17000000000000001,\n",
       "   'benchmark_total_returns': 0.89300000000000002,\n",
       "   'beta': 0.94699999999999995,\n",
       "   'cash': 2080687.6529999999,\n",
       "   'downside_risk': 0.035999999999999997,\n",
       "   'end_date': '2018-01-22',\n",
       "   'information_ratio': 0.95199999999999996,\n",
       "   'max_drawdown': 0.40799999999999997,\n",
       "   'run_type': 'BACKTEST',\n",
       "   'sharpe': 0.81999999999999995,\n",
       "   'sortino': 5.4530000000000003,\n",
       "   'start_date': '2014-01-03',\n",
       "   'strategy_file': 'strategy.py',\n",
       "   'strategy_name': 'strategy',\n",
       "   'total_returns': 1.323,\n",
       "   'total_value': 23225390.339000002,\n",
       "   'tracking_error': 0.056000000000000001,\n",
       "   'unit_net_value': 2.323,\n",
       "   'units': 10000000.0,\n",
       "   'volatility': 0.23899999999999999},\n",
       "  'trades':                      commission     exec_id  last_price  last_quantity  \\\n",
       "  datetime                                                                 \n",
       "  2014-01-03 15:00:00      5.0000  1516788432       11.93          300.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788433        7.84          400.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788434       20.19          100.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788435       14.07          200.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788436        5.15          700.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788437        5.33          600.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788438       18.33          200.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788439        7.50          400.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788440        9.74          300.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788441       30.99          100.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788442        7.92          400.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788443       12.10          300.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788444        4.68          700.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788445        7.15          500.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788446       10.50          300.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788447        6.92          500.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788448        6.82          500.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788449       19.06          100.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788450        9.64          300.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788451       24.60          100.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788452        9.14          400.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788453        4.98          700.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788454        7.61          400.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788455        4.01          900.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788456        2.99         1200.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788457        4.38          800.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788458        2.70         1300.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788459        8.11          400.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788460       17.65          200.0   \n",
       "  2014-01-03 15:00:00      5.0000  1516788461        3.94          900.0   \n",
       "  ...                         ...         ...         ...            ...   \n",
       "  2017-09-29 15:00:00      7.5432  1516879289       31.43          300.0   \n",
       "  2017-09-29 15:00:00      6.8992  1516879290        6.16         1400.0   \n",
       "  2017-09-29 15:00:00      7.8560  1516879291        9.82         1000.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879292        6.31          100.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879293       15.09          100.0   \n",
       "  2017-09-29 15:00:00     10.8240  1516879294       22.55          600.0   \n",
       "  2017-09-29 15:00:00      7.7024  1516879295        3.32         2900.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879296        8.30          100.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879297       21.39          200.0   \n",
       "  2017-09-29 15:00:00      7.0000  1516879298        8.75         1000.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879299        7.91          100.0   \n",
       "  2017-09-29 15:00:00      6.2784  1516879300        8.72          900.0   \n",
       "  2017-09-29 15:00:00      5.7184  1516879301       17.87          400.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879302        7.46          400.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879303        3.82          200.0   \n",
       "  2017-09-29 15:00:00      9.0672  1516879304       56.67          200.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879305        6.00          100.0   \n",
       "  2017-09-29 15:00:00      5.9088  1516879306       36.93          200.0   \n",
       "  2017-09-29 15:00:00      7.5968  1516879307       23.74          400.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879308        5.12          100.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879309        9.28          100.0   \n",
       "  2017-09-29 15:00:00      7.7088  1516879310        8.03         1200.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879311       22.62          100.0   \n",
       "  2017-09-29 15:00:00      6.4160  1516879312        8.02         1000.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879313        4.05          200.0   \n",
       "  2017-09-29 15:00:00      7.0312  1516879314        7.99         1100.0   \n",
       "  2017-09-29 15:00:00      6.6144  1516879315        6.89         1200.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879316        7.99          200.0   \n",
       "  2017-09-29 15:00:00      7.2512  1516879317        4.12         2200.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516879318        6.35          700.0   \n",
       "  \n",
       "                      order_book_id    order_id position_effect  side symbol  \\\n",
       "  datetime                                                                     \n",
       "  2014-01-03 15:00:00   000001.XSHE  1516788430            None   BUY   平安银行   \n",
       "  2014-01-03 15:00:00   000002.XSHE  1516788431            None   BUY    万科A   \n",
       "  2014-01-03 15:00:00   000024.XSHE  1516788432            None   BUY   招商地产   \n",
       "  2014-01-03 15:00:00   000063.XSHE  1516788433            None   BUY   中兴通讯   \n",
       "  2014-01-03 15:00:00   000069.XSHE  1516788434            None   BUY   华侨城A   \n",
       "  2014-01-03 15:00:00   000157.XSHE  1516788435            None   BUY   中联重科   \n",
       "  2014-01-03 15:00:00   000338.XSHE  1516788436            None   BUY   潍柴动力   \n",
       "  2014-01-03 15:00:00   000425.XSHE  1516788437            None   BUY   徐工机械   \n",
       "  2014-01-03 15:00:00   000630.XSHE  1516788438            None   BUY   铜陵有色   \n",
       "  2014-01-03 15:00:00   000651.XSHE  1516788439            None   BUY   格力电器   \n",
       "  2014-01-03 15:00:00   000656.XSHE  1516788440            None   BUY   金科股份   \n",
       "  2014-01-03 15:00:00   000776.XSHE  1516788441            None   BUY   广发证券   \n",
       "  2014-01-03 15:00:00   000933.XSHE  1516788442            None   BUY   神火股份   \n",
       "  2014-01-03 15:00:00   000937.XSHE  1516788443            None   BUY   冀中能源   \n",
       "  2014-01-03 15:00:00   000960.XSHE  1516788444            None   BUY   锡业股份   \n",
       "  2014-01-03 15:00:00   000961.XSHE  1516788445            None   BUY   中南建设   \n",
       "  2014-01-03 15:00:00   000983.XSHE  1516788446            None   BUY   西山煤电   \n",
       "  2014-01-03 15:00:00   002001.XSHE  1516788447            None   BUY    新和成   \n",
       "  2014-01-03 15:00:00   002299.XSHE  1516788448            None   BUY   圣农发展   \n",
       "  2014-01-03 15:00:00   002375.XSHE  1516788449            None   BUY   亚厦股份   \n",
       "  2014-01-03 15:00:00   600000.XSHG  1516788450            None   BUY   浦发银行   \n",
       "  2014-01-03 15:00:00   600011.XSHG  1516788451            None   BUY   华能国际   \n",
       "  2014-01-03 15:00:00   600016.XSHG  1516788452            None   BUY   民生银行   \n",
       "  2014-01-03 15:00:00   600019.XSHG  1516788453            None   BUY   宝钢股份   \n",
       "  2014-01-03 15:00:00   600027.XSHG  1516788454            None   BUY   华电国际   \n",
       "  2014-01-03 15:00:00   600028.XSHG  1516788455            None   BUY   中国石化   \n",
       "  2014-01-03 15:00:00   600029.XSHG  1516788456            None   BUY   南方航空   \n",
       "  2014-01-03 15:00:00   600048.XSHG  1516788457            None   BUY   保利地产   \n",
       "  2014-01-03 15:00:00   600066.XSHG  1516788458            None   BUY   宇通客车   \n",
       "  2014-01-03 15:00:00   600068.XSHG  1516788459            None   BUY    葛洲坝   \n",
       "  ...                           ...         ...             ...   ...    ...   \n",
       "  2017-09-29 15:00:00   600547.XSHG  1516885050            None   BUY   山东黄金   \n",
       "  2017-09-29 15:00:00   600583.XSHG  1516885051            None   BUY   海油工程   \n",
       "  2017-09-29 15:00:00   600649.XSHG  1516885052            None   BUY   城投控股   \n",
       "  2017-09-29 15:00:00   600688.XSHG  1516885053            None   BUY   上海石化   \n",
       "  2017-09-29 15:00:00   600690.XSHG  1516885054            None  SELL   青岛海尔   \n",
       "  2017-09-29 15:00:00   600741.XSHG  1516885055            None  SELL   华域汽车   \n",
       "  2017-09-29 15:00:00   600795.XSHG  1516885056            None   BUY   国电电力   \n",
       "  2017-09-29 15:00:00   600919.XSHG  1516885057            None  SELL   江苏银行   \n",
       "  2017-09-29 15:00:00   600999.XSHG  1516885058            None   BUY   招商证券   \n",
       "  2017-09-29 15:00:00   601006.XSHG  1516885059            None   BUY   大秦铁路   \n",
       "  2017-09-29 15:00:00   601009.XSHG  1516885060            None  SELL   南京银行   \n",
       "  2017-09-29 15:00:00   601111.XSHG  1516885061            None   BUY   中国国航   \n",
       "  2017-09-29 15:00:00   601155.XSHG  1516885062            None  SELL   新城控股   \n",
       "  2017-09-29 15:00:00   601169.XSHG  1516885063            None  SELL   北京银行   \n",
       "  2017-09-29 15:00:00   601288.XSHG  1516885064            None   BUY   农业银行   \n",
       "  2017-09-29 15:00:00   601336.XSHG  1516885065            None   BUY   新华保险   \n",
       "  2017-09-29 15:00:00   601398.XSHG  1516885066            None   BUY   工商银行   \n",
       "  2017-09-29 15:00:00   601601.XSHG  1516885067            None   BUY   中国太保   \n",
       "  2017-09-29 15:00:00   601607.XSHG  1516885068            None  SELL   上海医药   \n",
       "  2017-09-29 15:00:00   601618.XSHG  1516885069            None  SELL   中国中冶   \n",
       "  2017-09-29 15:00:00   601668.XSHG  1516885071            None   BUY   中国建筑   \n",
       "  2017-09-29 15:00:00   601669.XSHG  1516885072            None   BUY   中国电建   \n",
       "  2017-09-29 15:00:00   601688.XSHG  1516885073            None  SELL   华泰证券   \n",
       "  2017-09-29 15:00:00   601727.XSHG  1516885074            None  SELL   上海电气   \n",
       "  2017-09-29 15:00:00   601818.XSHG  1516885075            None   BUY   光大银行   \n",
       "  2017-09-29 15:00:00   601857.XSHG  1516885076            None  SELL   中国石油   \n",
       "  2017-09-29 15:00:00   601919.XSHG  1516885077            None   BUY   中远海控   \n",
       "  2017-09-29 15:00:00   601933.XSHG  1516885078            None  SELL   永辉超市   \n",
       "  2017-09-29 15:00:00   601988.XSHG  1516885079            None   BUY   中国银行   \n",
       "  2017-09-29 15:00:00   601992.XSHG  1516885080            None  SELL   金隅集团   \n",
       "  \n",
       "                          tax     trading_datetime  transaction_cost  \n",
       "  datetime                                                            \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            5.0000  \n",
       "  ...                     ...                  ...               ...  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            7.5432  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            6.8992  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            7.8560  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   1.509  2017-09-29 15:00:00            6.5090  \n",
       "  2017-09-29 15:00:00  13.530  2017-09-29 15:00:00           24.3540  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            7.7024  \n",
       "  2017-09-29 15:00:00   0.830  2017-09-29 15:00:00            5.8300  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            7.0000  \n",
       "  2017-09-29 15:00:00   0.791  2017-09-29 15:00:00            5.7910  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            6.2784  \n",
       "  2017-09-29 15:00:00   7.148  2017-09-29 15:00:00           12.8664  \n",
       "  2017-09-29 15:00:00   2.984  2017-09-29 15:00:00            7.9840  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            9.0672  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.9088  \n",
       "  2017-09-29 15:00:00   9.496  2017-09-29 15:00:00           17.0928  \n",
       "  2017-09-29 15:00:00   0.512  2017-09-29 15:00:00            5.5120  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            7.7088  \n",
       "  2017-09-29 15:00:00   2.262  2017-09-29 15:00:00            7.2620  \n",
       "  2017-09-29 15:00:00   8.020  2017-09-29 15:00:00           14.4360  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   8.789  2017-09-29 15:00:00           15.8202  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            6.6144  \n",
       "  2017-09-29 15:00:00   1.598  2017-09-29 15:00:00            6.5980  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            7.2512  \n",
       "  2017-09-29 15:00:00   4.445  2017-09-29 15:00:00            9.4450  \n",
       "  \n",
       "  [90887 rows x 12 columns]}}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import rqalpha\n",
    "from rqalpha.api import *\n",
    "\n",
    "#读取文件位置\n",
    "def init(context):\n",
    "    context.codes = Union_weight\n",
    "    context.stocks = None\n",
    "    context.pos_weight = 0.9\n",
    "    scheduler.run_daily(find_pool)\n",
    "    \n",
    "\n",
    "def find_pool(context, bar_dict):\n",
    "    try:\n",
    "        codes = context.codes.loc[context.now].dropna()\n",
    "        context.stocks = codes\n",
    "    except:\n",
    "        context.stocks = None\n",
    "\n",
    "def handle_bar(context, bar_dict):\n",
    "    buy(context, bar_dict)\n",
    "\n",
    "\n",
    "def buy(context, bar_dict):\n",
    "    pool = context.stocks\n",
    "    if pool is not None:\n",
    "        for ins, percentage in pool.items():\n",
    "            order_target_percent(ins, percentage*context.pos_weight)\n",
    "        for ins in context.portfolio.positions:\n",
    "            if ins not in context.stocks:\n",
    "                order_target_percent(ins, 0)\n",
    "\n",
    "config = {\n",
    "  \"base\": {\n",
    "    \"start_date\": \"2014-01-03\",\n",
    "    \"end_date\": \"2018-01-31\",\n",
    "    \"accounts\": {'stock':10000000},\n",
    "    \"benchmark\": \"000300.XSHG\"\n",
    "  },\n",
    "  \"extra\": {\n",
    "    \"log_level\": \"error\",\n",
    "  },\n",
    "    \n",
    "  \"mod\": {\n",
    "    \"sys_analyser\": {\n",
    "      #\"enabled\": True,\n",
    "      \"plot\": True\n",
    "    }\n",
    "  }\n",
    "}\n",
    "\n",
    "rqalpha.run_func(init=init, handle_bar=handle_bar, config=config)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "交集组合（不对冲）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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q+vfvj5GREY6OjrRr1461a9fmmKbVaomPj+fRo0eYmpqSmJjIuHHj+Oabb/K2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\nkkd8VE+ZxbB2J4bV4eVUjZWGVhdRRg0zUqPYeqSOI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ydH89JnxcHtrkk+u1JY0kRDi4sr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\n4Y8802lOGO7Q0GRj0/4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FBMOTjFw8Jpa/fLybcnOL9xgPXDXc2+nQYnOybm8FxdVNbMit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\nQCj8BkxCshc4bw9MAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f63b034b400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'sys_analyser': {'benchmark_portfolio':              cash  market_value  static_unit_net_value  total_value  \\\n",
       "  date                                                                  \n",
       "  2014-01-03  745.3    9999254.70                  1.000  10000000.00   \n",
       "  2014-01-06  745.3    9771663.60                  1.000   9772408.90   \n",
       "  2014-01-07  745.3    9768870.00                  0.977   9769615.30   \n",
       "  2014-01-08  745.3    9785937.15                  0.977   9786682.45   \n",
       "  2014-01-09  745.3    9699990.30                  0.979   9700735.60   \n",
       "  2014-01-10  745.3    9624170.25                  0.970   9624915.55   \n",
       "  2014-01-13  745.3    9575413.20                  0.962   9576158.50   \n",
       "  2014-01-14  745.3    9659090.25                  0.958   9659835.55   \n",
       "  2014-01-15  745.3    9642023.10                  0.966   9642768.40   \n",
       "  2014-01-16  745.3    9654681.60                  0.964   9655426.90   \n",
       "  2014-01-17  745.3    9509108.85                  0.966   9509854.15   \n",
       "  2014-01-20  745.3    9454546.35                  0.951   9455291.65   \n",
       "  2014-01-21  745.3    9548044.65                  0.946   9548789.95   \n",
       "  2014-01-22  745.3    9794187.00                  0.955   9794932.30   \n",
       "  2014-01-23  745.3    9742199.85                  0.979   9742945.15   \n",
       "  2014-01-24  745.3    9802393.20                  0.974   9803138.50   \n",
       "  2014-01-27  745.3    9672490.80                  0.980   9673236.10   \n",
       "  2014-01-28  745.3    9689688.90                  0.967   9690434.20   \n",
       "  2014-01-29  745.3    9724259.70                  0.969   9725005.00   \n",
       "  2014-01-30  745.3    9613694.25                  0.973   9614439.55   \n",
       "  2014-02-07  745.3    9657475.20                  0.961   9658220.50   \n",
       "  2014-02-10  745.3    9897768.45                  0.966   9898513.75   \n",
       "  2014-02-11  745.3    9976469.40                  0.990   9977214.70   \n",
       "  2014-02-12  745.3   10001306.25                  0.998  10002051.55   \n",
       "  2014-02-13  745.3    9950235.75                  1.000   9950981.05   \n",
       "  2014-02-14  745.3   10020206.70                  0.995  10020952.00   \n",
       "  2014-02-17  745.3   10090352.25                  1.002  10091097.55   \n",
       "  2014-02-18  745.3    9962850.60                  1.009   9963595.90   \n",
       "  2014-02-19  745.3   10077300.90                  0.996  10078046.20   \n",
       "  2014-02-20  745.3    9984675.60                  1.008   9985420.90   \n",
       "  ...           ...           ...                    ...          ...   \n",
       "  2017-12-11  745.3   17763367.50                  1.748  17764112.80   \n",
       "  2017-12-12  745.3   17529927.30                  1.776  17530672.60   \n",
       "  2017-12-13  745.3   17678642.85                  1.753  17679388.15   \n",
       "  2017-12-14  745.3   17574144.75                  1.768  17574890.05   \n",
       "  2017-12-15  745.3   17376453.90                  1.757  17377199.20   \n",
       "  2017-12-18  745.3   17395790.85                  1.738  17396536.15   \n",
       "  2017-12-19  745.3   17614215.45                  1.740  17614960.75   \n",
       "  2017-12-20  745.3   17593088.85                  1.761  17593834.15   \n",
       "  2017-12-21  745.3   17756165.25                  1.759  17756910.55   \n",
       "  2017-12-22  745.3   17698329.00                  1.776  17699074.30   \n",
       "  2017-12-25  745.3   17641322.10                  1.770  17642067.40   \n",
       "  2017-12-26  745.3   17694051.30                  1.764  17694796.60   \n",
       "  2017-12-27  745.3   17421631.65                  1.769  17422376.95   \n",
       "  2017-12-28  745.3   17542498.50                  1.742  17543243.80   \n",
       "  2017-12-29  745.3   17594660.25                  1.754  17595405.55   \n",
       "  2018-01-02  745.3   17841501.00                  1.760  17842246.30   \n",
       "  2018-01-03  745.3   17946217.35                  1.784  17946962.65   \n",
       "  2018-01-04  745.3   18022255.65                  1.795  18023000.95   \n",
       "  2018-01-05  745.3   18065643.75                  1.802  18066389.05   \n",
       "  2018-01-08  745.3   18159098.40                  1.807  18159843.70   \n",
       "  2018-01-09  745.3   18286294.50                  1.816  18287039.80   \n",
       "  2018-01-10  745.3   18367090.65                  1.829  18367835.95   \n",
       "  2018-01-11  745.3   18357400.35                  1.837  18358145.65   \n",
       "  2018-01-12  745.3   18442125.00                  1.836  18442870.30   \n",
       "  2018-01-15  745.3   18443172.60                  1.844  18443917.90   \n",
       "  2018-01-16  745.3   18588221.55                  1.844  18588966.85   \n",
       "  2018-01-17  745.3   18543043.80                  1.859  18543789.10   \n",
       "  2018-01-18  745.3   18644748.30                  1.854  18645493.60   \n",
       "  2018-01-19  745.3   18705771.00                  1.865  18706516.30   \n",
       "  2018-01-22  745.3   18929259.00                  1.871  18930004.30   \n",
       "  \n",
       "              unit_net_value       units  \n",
       "  date                                    \n",
       "  2014-01-03        1.000000  10000000.0  \n",
       "  2014-01-06        0.977241  10000000.0  \n",
       "  2014-01-07        0.976962  10000000.0  \n",
       "  2014-01-08        0.978668  10000000.0  \n",
       "  2014-01-09        0.970074  10000000.0  \n",
       "  2014-01-10        0.962492  10000000.0  \n",
       "  2014-01-13        0.957616  10000000.0  \n",
       "  2014-01-14        0.965984  10000000.0  \n",
       "  2014-01-15        0.964277  10000000.0  \n",
       "  2014-01-16        0.965543  10000000.0  \n",
       "  2014-01-17        0.950985  10000000.0  \n",
       "  2014-01-20        0.945529  10000000.0  \n",
       "  2014-01-21        0.954879  10000000.0  \n",
       "  2014-01-22        0.979493  10000000.0  \n",
       "  2014-01-23        0.974295  10000000.0  \n",
       "  2014-01-24        0.980314  10000000.0  \n",
       "  2014-01-27        0.967324  10000000.0  \n",
       "  2014-01-28        0.969043  10000000.0  \n",
       "  2014-01-29        0.972500  10000000.0  \n",
       "  2014-01-30        0.961444  10000000.0  \n",
       "  2014-02-07        0.965822  10000000.0  \n",
       "  2014-02-10        0.989851  10000000.0  \n",
       "  2014-02-11        0.997721  10000000.0  \n",
       "  2014-02-12        1.000205  10000000.0  \n",
       "  2014-02-13        0.995098  10000000.0  \n",
       "  2014-02-14        1.002095  10000000.0  \n",
       "  2014-02-17        1.009110  10000000.0  \n",
       "  2014-02-18        0.996360  10000000.0  \n",
       "  2014-02-19        1.007805  10000000.0  \n",
       "  2014-02-20        0.998542  10000000.0  \n",
       "  ...                    ...         ...  \n",
       "  2017-12-11        1.776411  10000000.0  \n",
       "  2017-12-12        1.753067  10000000.0  \n",
       "  2017-12-13        1.767939  10000000.0  \n",
       "  2017-12-14        1.757489  10000000.0  \n",
       "  2017-12-15        1.737720  10000000.0  \n",
       "  2017-12-18        1.739654  10000000.0  \n",
       "  2017-12-19        1.761496  10000000.0  \n",
       "  2017-12-20        1.759383  10000000.0  \n",
       "  2017-12-21        1.775691  10000000.0  \n",
       "  2017-12-22        1.769907  10000000.0  \n",
       "  2017-12-25        1.764207  10000000.0  \n",
       "  2017-12-26        1.769480  10000000.0  \n",
       "  2017-12-27        1.742238  10000000.0  \n",
       "  2017-12-28        1.754324  10000000.0  \n",
       "  2017-12-29        1.759541  10000000.0  \n",
       "  2018-01-02        1.784225  10000000.0  \n",
       "  2018-01-03        1.794696  10000000.0  \n",
       "  2018-01-04        1.802300  10000000.0  \n",
       "  2018-01-05        1.806639  10000000.0  \n",
       "  2018-01-08        1.815984  10000000.0  \n",
       "  2018-01-09        1.828704  10000000.0  \n",
       "  2018-01-10        1.836784  10000000.0  \n",
       "  2018-01-11        1.835815  10000000.0  \n",
       "  2018-01-12        1.844287  10000000.0  \n",
       "  2018-01-15        1.844392  10000000.0  \n",
       "  2018-01-16        1.858897  10000000.0  \n",
       "  2018-01-17        1.854379  10000000.0  \n",
       "  2018-01-18        1.864549  10000000.0  \n",
       "  2018-01-19        1.870652  10000000.0  \n",
       "  2018-01-22        1.893000  10000000.0  \n",
       "  \n",
       "  [991 rows x 6 columns],\n",
       "  'portfolio':                    cash  market_value  static_unit_net_value   total_value  \\\n",
       "  date                                                                         \n",
       "  2014-01-03  9706814.639      292951.0                  1.000  9.999766e+06   \n",
       "  2014-01-06  9400250.633      588600.0                  1.000  9.988851e+06   \n",
       "  2014-01-07  9097252.082      888252.0                  0.999  9.985504e+06   \n",
       "  2014-01-08  8790795.296     1184237.0                  0.999  9.975032e+06   \n",
       "  2014-01-09  8489710.813     1481302.0                  0.998  9.971013e+06   \n",
       "  2014-01-10  8182080.859     1779354.0                  0.997  9.961435e+06   \n",
       "  2014-01-13  7880399.282     2080951.0                  0.996  9.961350e+06   \n",
       "  2014-01-14  7599941.843     2387894.0                  0.996  9.987836e+06   \n",
       "  2014-01-15  7291149.545     2677272.0                  0.999  9.968422e+06   \n",
       "  2014-01-16  6996340.950     2986255.0                  0.997  9.982596e+06   \n",
       "  2014-01-17  6661888.389     3254564.0                  0.998  9.916452e+06   \n",
       "  2014-01-20  6355107.321     3551897.0                  0.992  9.907004e+06   \n",
       "  2014-01-21  6079724.333     3876236.0                  0.991  9.955960e+06   \n",
       "  2014-01-22  5845479.047     4241201.0                  0.996  1.008668e+07   \n",
       "  2014-01-23  5548529.215     4526813.0                  1.009  1.007534e+07   \n",
       "  2014-01-24  5270485.822     4863555.0                  1.008  1.013404e+07   \n",
       "  2014-01-27  4958876.846     5141871.0                  1.013  1.010075e+07   \n",
       "  2014-01-28  4651822.386     5440396.0                  1.010  1.009222e+07   \n",
       "  2014-01-29  4346044.717     5739011.0                  1.009  1.008506e+07   \n",
       "  2014-01-30  4017434.893     5993738.0                  1.009  1.001117e+07   \n",
       "  2014-02-07  3722365.004     6314626.0                  1.001  1.003699e+07   \n",
       "  2014-02-10  3470981.563     6737591.0                  1.004  1.020857e+07   \n",
       "  2014-02-11  3198998.643     7110104.0                  1.021  1.030910e+07   \n",
       "  2014-02-12  2895827.550     7430784.0                  1.031  1.033577e+07   \n",
       "  2014-02-13  2574217.692     7709081.0                  1.034  1.029246e+07   \n",
       "  2014-02-14  2271575.357     8065363.0                  1.029  1.034610e+07   \n",
       "  2014-02-17  1974072.891     8448710.0                  1.035  1.043194e+07   \n",
       "  2014-02-18  1672747.236     8690358.0                  1.043  1.036311e+07   \n",
       "  2014-02-19  1367064.606     9092066.0                  1.036  1.045913e+07   \n",
       "  2014-02-20  1050392.931     9398328.0                  1.046  1.044872e+07   \n",
       "  ...                 ...           ...                    ...           ...   \n",
       "  2017-12-11  2606790.021    23945797.2                  2.633  2.655259e+07   \n",
       "  2017-12-12  2606790.021    23663386.4                  2.655  2.627018e+07   \n",
       "  2017-12-13  2606790.021    23759139.2                  2.627  2.636593e+07   \n",
       "  2017-12-14  2606790.021    23637444.4                  2.637  2.624423e+07   \n",
       "  2017-12-15  2606790.021    23401336.0                  2.624  2.600813e+07   \n",
       "  2017-12-18  2606790.021    23426004.8                  2.601  2.603279e+07   \n",
       "  2017-12-19  2606790.021    23624215.6                  2.603  2.623101e+07   \n",
       "  2017-12-20  2606790.021    23529207.4                  2.623  2.613600e+07   \n",
       "  2017-12-21  2606790.021    23645443.8                  2.614  2.625223e+07   \n",
       "  2017-12-22  2606790.021    23656957.2                  2.625  2.626375e+07   \n",
       "  2017-12-25  2606790.021    23681250.6                  2.626  2.628804e+07   \n",
       "  2017-12-26  2606790.021    23929450.2                  2.629  2.653624e+07   \n",
       "  2017-12-27  2606790.021    23693308.2                  2.654  2.630010e+07   \n",
       "  2017-12-28  2606790.021    23690926.2                  2.630  2.629772e+07   \n",
       "  2017-12-29  2606790.021    23880349.0                  2.630  2.648714e+07   \n",
       "  2018-01-02  2606790.021    24335536.2                  2.649  2.694233e+07   \n",
       "  2018-01-03  2606790.021    24484148.6                  2.694  2.709094e+07   \n",
       "  2018-01-04  2606790.021    24546201.0                  2.709  2.715299e+07   \n",
       "  2018-01-05  2606790.021    24681348.2                  2.715  2.728814e+07   \n",
       "  2018-01-08  2606790.021    24838762.8                  2.729  2.744555e+07   \n",
       "  2018-01-09  2606790.021    24726222.8                  2.745  2.733301e+07   \n",
       "  2018-01-10  2606790.021    24846222.0                  2.733  2.745301e+07   \n",
       "  2018-01-11  2606790.021    24787750.8                  2.745  2.739454e+07   \n",
       "  2018-01-12  2606790.021    24875049.2                  2.739  2.748184e+07   \n",
       "  2018-01-15  2606790.021    24960305.0                  2.748  2.756710e+07   \n",
       "  2018-01-16  2606790.021    25245469.4                  2.757  2.785226e+07   \n",
       "  2018-01-17  2606790.021    25386899.4                  2.785  2.799369e+07   \n",
       "  2018-01-18  2606790.021    25697584.0                  2.799  2.830437e+07   \n",
       "  2018-01-19  2606790.021    25778644.6                  2.830  2.838543e+07   \n",
       "  2018-01-22  2606790.021    25703953.4                  2.839  2.831074e+07   \n",
       "  \n",
       "              unit_net_value       units  \n",
       "  date                                    \n",
       "  2014-01-03        0.999977  10000000.0  \n",
       "  2014-01-06        0.998885  10000000.0  \n",
       "  2014-01-07        0.998550  10000000.0  \n",
       "  2014-01-08        0.997503  10000000.0  \n",
       "  2014-01-09        0.997101  10000000.0  \n",
       "  2014-01-10        0.996143  10000000.0  \n",
       "  2014-01-13        0.996135  10000000.0  \n",
       "  2014-01-14        0.998784  10000000.0  \n",
       "  2014-01-15        0.996842  10000000.0  \n",
       "  2014-01-16        0.998260  10000000.0  \n",
       "  2014-01-17        0.991645  10000000.0  \n",
       "  2014-01-20        0.990700  10000000.0  \n",
       "  2014-01-21        0.995596  10000000.0  \n",
       "  2014-01-22        1.008668  10000000.0  \n",
       "  2014-01-23        1.007534  10000000.0  \n",
       "  2014-01-24        1.013404  10000000.0  \n",
       "  2014-01-27        1.010075  10000000.0  \n",
       "  2014-01-28        1.009222  10000000.0  \n",
       "  2014-01-29        1.008506  10000000.0  \n",
       "  2014-01-30        1.001117  10000000.0  \n",
       "  2014-02-07        1.003699  10000000.0  \n",
       "  2014-02-10        1.020857  10000000.0  \n",
       "  2014-02-11        1.030910  10000000.0  \n",
       "  2014-02-12        1.033577  10000000.0  \n",
       "  2014-02-13        1.029246  10000000.0  \n",
       "  2014-02-14        1.034610  10000000.0  \n",
       "  2014-02-17        1.043194  10000000.0  \n",
       "  2014-02-18        1.036311  10000000.0  \n",
       "  2014-02-19        1.045913  10000000.0  \n",
       "  2014-02-20        1.044872  10000000.0  \n",
       "  ...                    ...         ...  \n",
       "  2017-12-11        2.655259  10000000.0  \n",
       "  2017-12-12        2.627018  10000000.0  \n",
       "  2017-12-13        2.636593  10000000.0  \n",
       "  2017-12-14        2.624423  10000000.0  \n",
       "  2017-12-15        2.600813  10000000.0  \n",
       "  2017-12-18        2.603279  10000000.0  \n",
       "  2017-12-19        2.623101  10000000.0  \n",
       "  2017-12-20        2.613600  10000000.0  \n",
       "  2017-12-21        2.625223  10000000.0  \n",
       "  2017-12-22        2.626375  10000000.0  \n",
       "  2017-12-25        2.628804  10000000.0  \n",
       "  2017-12-26        2.653624  10000000.0  \n",
       "  2017-12-27        2.630010  10000000.0  \n",
       "  2017-12-28        2.629772  10000000.0  \n",
       "  2017-12-29        2.648714  10000000.0  \n",
       "  2018-01-02        2.694233  10000000.0  \n",
       "  2018-01-03        2.709094  10000000.0  \n",
       "  2018-01-04        2.715299  10000000.0  \n",
       "  2018-01-05        2.728814  10000000.0  \n",
       "  2018-01-08        2.744555  10000000.0  \n",
       "  2018-01-09        2.733301  10000000.0  \n",
       "  2018-01-10        2.745301  10000000.0  \n",
       "  2018-01-11        2.739454  10000000.0  \n",
       "  2018-01-12        2.748184  10000000.0  \n",
       "  2018-01-15        2.756710  10000000.0  \n",
       "  2018-01-16        2.785226  10000000.0  \n",
       "  2018-01-17        2.799369  10000000.0  \n",
       "  2018-01-18        2.830437  10000000.0  \n",
       "  2018-01-19        2.838543  10000000.0  \n",
       "  2018-01-22        2.831074  10000000.0  \n",
       "  \n",
       "  [991 rows x 6 columns],\n",
       "  'stock_account':                    cash  dividend_receivable  market_value   total_value  \\\n",
       "  date                                                                       \n",
       "  2014-01-03  9706814.639                  0.0      292951.0  9.999766e+06   \n",
       "  2014-01-06  9400250.633                  0.0      588600.0  9.988851e+06   \n",
       "  2014-01-07  9097252.082                  0.0      888252.0  9.985504e+06   \n",
       "  2014-01-08  8790795.296                  0.0     1184237.0  9.975032e+06   \n",
       "  2014-01-09  8489710.813                  0.0     1481302.0  9.971013e+06   \n",
       "  2014-01-10  8182080.859                  0.0     1779354.0  9.961435e+06   \n",
       "  2014-01-13  7880399.282                  0.0     2080951.0  9.961350e+06   \n",
       "  2014-01-14  7599941.843                  0.0     2387894.0  9.987836e+06   \n",
       "  2014-01-15  7291149.545                  0.0     2677272.0  9.968422e+06   \n",
       "  2014-01-16  6996340.950                  0.0     2986255.0  9.982596e+06   \n",
       "  2014-01-17  6661888.389                  0.0     3254564.0  9.916452e+06   \n",
       "  2014-01-20  6355107.321                  0.0     3551897.0  9.907004e+06   \n",
       "  2014-01-21  6079724.333                  0.0     3876236.0  9.955960e+06   \n",
       "  2014-01-22  5845479.047                  0.0     4241201.0  1.008668e+07   \n",
       "  2014-01-23  5548529.215                  0.0     4526813.0  1.007534e+07   \n",
       "  2014-01-24  5270485.822                  0.0     4863555.0  1.013404e+07   \n",
       "  2014-01-27  4958876.846                  0.0     5141871.0  1.010075e+07   \n",
       "  2014-01-28  4651822.386                  0.0     5440396.0  1.009222e+07   \n",
       "  2014-01-29  4346044.717                  0.0     5739011.0  1.008506e+07   \n",
       "  2014-01-30  4017434.893                  0.0     5993738.0  1.001117e+07   \n",
       "  2014-02-07  3722365.004                  0.0     6314626.0  1.003699e+07   \n",
       "  2014-02-10  3470981.563                  0.0     6737591.0  1.020857e+07   \n",
       "  2014-02-11  3198998.643                  0.0     7110104.0  1.030910e+07   \n",
       "  2014-02-12  2895827.550               9160.0     7430784.0  1.033577e+07   \n",
       "  2014-02-13  2574217.692               9160.0     7709081.0  1.029246e+07   \n",
       "  2014-02-14  2271575.357               9160.0     8065363.0  1.034610e+07   \n",
       "  2014-02-17  1974072.891               9160.0     8448710.0  1.043194e+07   \n",
       "  2014-02-18  1672747.236                  0.0     8690358.0  1.036311e+07   \n",
       "  2014-02-19  1367064.606                  0.0     9092066.0  1.045913e+07   \n",
       "  2014-02-20  1050392.931                  0.0     9398328.0  1.044872e+07   \n",
       "  ...                 ...                  ...           ...           ...   \n",
       "  2017-12-11  2606790.021                  0.0    23945797.2  2.655259e+07   \n",
       "  2017-12-12  2606790.021                  0.0    23663386.4  2.627018e+07   \n",
       "  2017-12-13  2606790.021                  0.0    23759139.2  2.636593e+07   \n",
       "  2017-12-14  2606790.021                  0.0    23637444.4  2.624423e+07   \n",
       "  2017-12-15  2606790.021                  0.0    23401336.0  2.600813e+07   \n",
       "  2017-12-18  2606790.021                  0.0    23426004.8  2.603279e+07   \n",
       "  2017-12-19  2606790.021                  0.0    23624215.6  2.623101e+07   \n",
       "  2017-12-20  2606790.021                  0.0    23529207.4  2.613600e+07   \n",
       "  2017-12-21  2606790.021                  0.0    23645443.8  2.625223e+07   \n",
       "  2017-12-22  2606790.021                  0.0    23656957.2  2.626375e+07   \n",
       "  2017-12-25  2606790.021                  0.0    23681250.6  2.628804e+07   \n",
       "  2017-12-26  2606790.021                  0.0    23929450.2  2.653624e+07   \n",
       "  2017-12-27  2606790.021                  0.0    23693308.2  2.630010e+07   \n",
       "  2017-12-28  2606790.021                  0.0    23690926.2  2.629772e+07   \n",
       "  2017-12-29  2606790.021                  0.0    23880349.0  2.648714e+07   \n",
       "  2018-01-02  2606790.021                  0.0    24335536.2  2.694233e+07   \n",
       "  2018-01-03  2606790.021                  0.0    24484148.6  2.709094e+07   \n",
       "  2018-01-04  2606790.021                  0.0    24546201.0  2.715299e+07   \n",
       "  2018-01-05  2606790.021                  0.0    24681348.2  2.728814e+07   \n",
       "  2018-01-08  2606790.021                  0.0    24838762.8  2.744555e+07   \n",
       "  2018-01-09  2606790.021                  0.0    24726222.8  2.733301e+07   \n",
       "  2018-01-10  2606790.021                  0.0    24846222.0  2.745301e+07   \n",
       "  2018-01-11  2606790.021                  0.0    24787750.8  2.739454e+07   \n",
       "  2018-01-12  2606790.021                  0.0    24875049.2  2.748184e+07   \n",
       "  2018-01-15  2606790.021                  0.0    24960305.0  2.756710e+07   \n",
       "  2018-01-16  2606790.021                  0.0    25245469.4  2.785226e+07   \n",
       "  2018-01-17  2606790.021                  0.0    25386899.4  2.799369e+07   \n",
       "  2018-01-18  2606790.021                  0.0    25697584.0  2.830437e+07   \n",
       "  2018-01-19  2606790.021                  0.0    25778644.6  2.838543e+07   \n",
       "  2018-01-22  2606790.021                  0.0    25703953.4  2.831074e+07   \n",
       "  \n",
       "              transaction_cost  \n",
       "  date                          \n",
       "  2014-01-03           234.361  \n",
       "  2014-01-06           254.006  \n",
       "  2014-01-07           259.550  \n",
       "  2014-01-08           294.786  \n",
       "  2014-01-09           287.483  \n",
       "  2014-01-10           300.954  \n",
       "  2014-01-13           306.577  \n",
       "  2014-01-14           279.439  \n",
       "  2014-01-15           285.298  \n",
       "  2014-01-16           286.595  \n",
       "  2014-01-17           365.561  \n",
       "  2014-01-20           317.068  \n",
       "  2014-01-21           330.988  \n",
       "  2014-01-22           433.286  \n",
       "  2014-01-23           392.833  \n",
       "  2014-01-24           339.393  \n",
       "  2014-01-27           393.976  \n",
       "  2014-01-28           345.460  \n",
       "  2014-01-29           352.669  \n",
       "  2014-01-30           401.824  \n",
       "  2014-02-07           360.889  \n",
       "  2014-02-10           414.441  \n",
       "  2014-02-11           442.920  \n",
       "  2014-02-12           437.093  \n",
       "  2014-02-13           476.858  \n",
       "  2014-02-14           388.335  \n",
       "  2014-02-17           416.466  \n",
       "  2014-02-18           553.656  \n",
       "  2014-02-19           446.629  \n",
       "  2014-02-20           466.675  \n",
       "  ...                      ...  \n",
       "  2017-12-11             0.000  \n",
       "  2017-12-12             0.000  \n",
       "  2017-12-13             0.000  \n",
       "  2017-12-14             0.000  \n",
       "  2017-12-15             0.000  \n",
       "  2017-12-18             0.000  \n",
       "  2017-12-19             0.000  \n",
       "  2017-12-20             0.000  \n",
       "  2017-12-21             0.000  \n",
       "  2017-12-22             0.000  \n",
       "  2017-12-25             0.000  \n",
       "  2017-12-26             0.000  \n",
       "  2017-12-27             0.000  \n",
       "  2017-12-28             0.000  \n",
       "  2017-12-29             0.000  \n",
       "  2018-01-02             0.000  \n",
       "  2018-01-03             0.000  \n",
       "  2018-01-04             0.000  \n",
       "  2018-01-05             0.000  \n",
       "  2018-01-08             0.000  \n",
       "  2018-01-09             0.000  \n",
       "  2018-01-10             0.000  \n",
       "  2018-01-11             0.000  \n",
       "  2018-01-12             0.000  \n",
       "  2018-01-15             0.000  \n",
       "  2018-01-16             0.000  \n",
       "  2018-01-17             0.000  \n",
       "  2018-01-18             0.000  \n",
       "  2018-01-19             0.000  \n",
       "  2018-01-22             0.000  \n",
       "  \n",
       "  [991 rows x 5 columns],\n",
       "  'stock_positions':             avg_price  last_price  market_value order_book_id  quantity symbol\n",
       "  date                                                                          \n",
       "  2014-01-03     14.070       14.07       12663.0   000063.XSHE     900.0   中兴通讯\n",
       "  2014-01-03      6.920        6.92       12456.0   000961.XSHE    1800.0   中南建设\n",
       "  2014-01-03      6.820        6.82       12958.0   000983.XSHE    1900.0   西山煤电\n",
       "  2014-01-03      4.980        4.98       12948.0   600011.XSHG    2600.0   华能国际\n",
       "  2014-01-03      4.010        4.01       12832.0   600019.XSHG    3200.0   宝钢股份\n",
       "  2014-01-03      4.380        4.38       12702.0   600028.XSHG    2900.0   中国石化\n",
       "  2014-01-03     10.310       10.31       12372.0   600123.XSHG    1200.0   兰花科创\n",
       "  2014-01-03      5.330        5.33       12792.0   600157.XSHG    2400.0   永泰能源\n",
       "  2014-01-03      8.690        8.69       13035.0   600188.XSHG    1500.0   兖州煤业\n",
       "  2014-01-03      6.790        6.79       12901.0   600348.XSHG    1900.0   阳泉煤业\n",
       "  2014-01-03     14.360       14.36       12924.0   600362.XSHG     900.0   江西铜业\n",
       "  2014-01-03      6.940        6.94       12492.0   600395.XSHG    1800.0   盘江股份\n",
       "  2014-01-03      6.800        6.80       12920.0   600403.XSHG    1900.0  *ST大有\n",
       "  2014-01-03      4.840        4.84       12584.0   600546.XSHG    2600.0   山煤国际\n",
       "  2014-01-03      6.800        6.80       12920.0   600971.XSHG    1900.0   恒源煤电\n",
       "  2014-01-03      5.300        5.30       12720.0   600997.XSHG    2400.0   开滦股份\n",
       "  2014-01-03      7.000        7.00       12600.0   601101.XSHG    1800.0   昊华能源\n",
       "  2014-01-03      4.520        4.52       12656.0   601186.XSHG    2800.0   中国铁建\n",
       "  2014-01-03      5.090        5.09       12725.0   601258.XSHG    2500.0   庞大集团\n",
       "  2014-01-03      4.750        4.75       12825.0   601299.XSHG    2700.0   中国北车\n",
       "  2014-01-03      3.790        3.79       12886.0   601328.XSHG    3400.0   交通银行\n",
       "  2014-01-03     10.200       10.20       12240.0   601699.XSHG    1200.0   潞安环能\n",
       "  2014-01-03      2.560        2.56       12800.0   601988.XSHG    5000.0   中国银行\n",
       "  2014-01-06     13.863       13.63       23171.0   000063.XSHE    1700.0   中兴通讯\n",
       "  2014-01-06      6.765        6.61       23796.0   000961.XSHE    3600.0   中南建设\n",
       "  2014-01-06      6.683        6.53       23508.0   000983.XSHE    3600.0   西山煤电\n",
       "  2014-01-06      4.879        4.77       23850.0   600011.XSHG    5000.0   华能国际\n",
       "  2014-01-06      4.007        3.90       12870.0   600019.XSHG    3300.0   宝钢股份\n",
       "  2014-01-06      4.380        4.48       12992.0   600028.XSHG    2900.0   中国石化\n",
       "  2014-01-06     10.060        9.81       23544.0   600123.XSHG    2400.0   兰花科创\n",
       "  ...               ...         ...           ...           ...       ...    ...\n",
       "  2018-01-22     22.198       39.53       75107.0   000002.XSHE    1900.0    万科A\n",
       "  2018-01-22      4.318        5.42      382110.0   600208.XSHG   70500.0   新湖中宝\n",
       "  2018-01-22     52.463       78.74      464566.0   601318.XSHG    5900.0   中国平安\n",
       "  2018-01-22      6.871        9.06     1118910.0   601939.XSHG  123500.0   建设银行\n",
       "  2018-01-22     15.011       14.99      370253.0   601997.XSHG   24700.0   贵阳银行\n",
       "  2018-01-22     11.681       16.01      531532.0   600383.XSHG   33200.0   金地集团\n",
       "  2018-01-22     14.407       12.60      401940.0   600926.XSHG   31900.0   杭州银行\n",
       "  2018-01-22      6.423        7.12      308296.0   601998.XSHG   43300.0   中信银行\n",
       "  2018-01-22     18.023       15.73      202917.0   601229.XSHG   12900.0   上海银行\n",
       "  2018-01-22      5.051        4.52      124752.0   601618.XSHG   27600.0   中国中冶\n",
       "  2018-01-22      4.091        4.48      250432.0   601818.XSHG   55900.0   光大银行\n",
       "  2018-01-22     21.245       23.36      838624.0   600066.XSHG   35900.0   宇通客车\n",
       "  2018-01-22      6.417        6.65     1063335.0   600688.XSHG  159900.0   上海石化\n",
       "  2018-01-22      7.091        7.47      292077.0   601117.XSHG   39100.0   中国化学\n",
       "  2018-01-22      6.784        9.10       95550.0   000338.XSHE   10500.0   潍柴动力\n",
       "  2018-01-22     11.990       11.89      382858.0   600153.XSHG   32200.0   建发股份\n",
       "  2018-01-22      7.503        8.26      856562.0   000876.XSHE  103700.0    新希望\n",
       "  2018-01-22     10.030       10.14      718926.0   600089.XSHG   70900.0   特变电工\n",
       "  2018-01-22     23.470       32.99      567428.0   600585.XSHG   17200.0   海螺水泥\n",
       "  2018-01-22     10.213       12.66      174708.0   002146.XSHE   13800.0   荣盛发展\n",
       "  2018-01-22      4.133        4.40      913880.0   601988.XSHG  207700.0   中国银行\n",
       "  2018-01-22      6.956        5.84      156512.0   000415.XSHE   26800.0   渤海金控\n",
       "  2018-01-22      7.309        9.32      471592.0   600019.XSHG   50600.0   宝钢股份\n",
       "  2018-01-22     15.240       13.20       67320.0   600827.XSHG    5100.0   百联股份\n",
       "  2018-01-22     17.381       17.90      259550.0   601166.XSHG   14500.0   兴业银行\n",
       "  2018-01-22      5.938        7.17      258837.0   601398.XSHG   36100.0   工商银行\n",
       "  2018-01-22     25.885       33.08      258024.0   600036.XSHG    7800.0   招商银行\n",
       "  2018-01-22      8.089        7.68      205824.0   601669.XSHG   26800.0   中国电建\n",
       "  2018-01-22      7.894        9.29      140279.0   601009.XSHG   15100.0   南京银行\n",
       "  2018-01-22      3.320        3.21       68694.0   600795.XSHG   21400.0   国电电力\n",
       "  \n",
       "  [63607 rows x 6 columns],\n",
       "  'summary': {'STOCK': 10000000.0,\n",
       "   'alpha': 0.112,\n",
       "   'annualized_returns': 0.29199999999999998,\n",
       "   'benchmark': '000300.XSHG',\n",
       "   'benchmark_annualized_returns': 0.17000000000000001,\n",
       "   'benchmark_total_returns': 0.89300000000000002,\n",
       "   'beta': 0.88800000000000001,\n",
       "   'cash': 2606790.0210000002,\n",
       "   'downside_risk': 0.047,\n",
       "   'end_date': '2018-01-22',\n",
       "   'information_ratio': 1.242,\n",
       "   'max_drawdown': 0.34200000000000003,\n",
       "   'run_type': 'BACKTEST',\n",
       "   'sharpe': 1.0369999999999999,\n",
       "   'sortino': 5.077,\n",
       "   'start_date': '2014-01-03',\n",
       "   'strategy_file': 'strategy.py',\n",
       "   'strategy_name': 'strategy',\n",
       "   'total_returns': 1.831,\n",
       "   'total_value': 28310743.421,\n",
       "   'tracking_error': 0.076999999999999999,\n",
       "   'unit_net_value': 2.831,\n",
       "   'units': 10000000.0,\n",
       "   'volatility': 0.23000000000000001},\n",
       "  'trades':                      commission     exec_id  last_price  last_quantity  \\\n",
       "  datetime                                                                 \n",
       "  2014-01-03 15:00:00     10.1304  1516792677       14.07          900.0   \n",
       "  2014-01-03 15:00:00      9.9648  1516792678        6.92         1800.0   \n",
       "  2014-01-03 15:00:00     10.3664  1516792679        6.82         1900.0   \n",
       "  2014-01-03 15:00:00     10.3584  1516792680        4.98         2600.0   \n",
       "  2014-01-03 15:00:00     10.2656  1516792681        4.01         3200.0   \n",
       "  2014-01-03 15:00:00     10.1616  1516792682        4.38         2900.0   \n",
       "  2014-01-03 15:00:00      9.8976  1516792683       10.31         1200.0   \n",
       "  2014-01-03 15:00:00     10.2336  1516792684        5.33         2400.0   \n",
       "  2014-01-03 15:00:00     10.4280  1516792685        8.69         1500.0   \n",
       "  2014-01-03 15:00:00     10.3208  1516792686        6.79         1900.0   \n",
       "  2014-01-03 15:00:00     10.3392  1516792687       14.36          900.0   \n",
       "  2014-01-03 15:00:00      9.9936  1516792688        6.94         1800.0   \n",
       "  2014-01-03 15:00:00     10.3360  1516792689        6.80         1900.0   \n",
       "  2014-01-03 15:00:00     10.0672  1516792690        4.84         2600.0   \n",
       "  2014-01-03 15:00:00     10.3360  1516792691        6.80         1900.0   \n",
       "  2014-01-03 15:00:00     10.1760  1516792692        5.30         2400.0   \n",
       "  2014-01-03 15:00:00     10.0800  1516792693        7.00         1800.0   \n",
       "  2014-01-03 15:00:00     10.1248  1516792694        4.52         2800.0   \n",
       "  2014-01-03 15:00:00     10.1800  1516792695        5.09         2500.0   \n",
       "  2014-01-03 15:00:00     10.2600  1516792696        4.75         2700.0   \n",
       "  2014-01-03 15:00:00     10.3088  1516792697        3.79         3400.0   \n",
       "  2014-01-03 15:00:00      9.7920  1516792698       10.20         1200.0   \n",
       "  2014-01-03 15:00:00     10.2400  1516792699        2.56         5000.0   \n",
       "  2014-01-06 15:00:00      8.7232  1516792700       13.63          800.0   \n",
       "  2014-01-06 15:00:00      8.5680  1516792701        5.95         1800.0   \n",
       "  2014-01-06 15:00:00      9.5184  1516792702        6.61         1800.0   \n",
       "  2014-01-06 15:00:00      8.8808  1516792703        6.53         1700.0   \n",
       "  2014-01-06 15:00:00      9.1584  1516792704        4.77         2400.0   \n",
       "  2014-01-06 15:00:00      5.0000  1516792705        3.90          100.0   \n",
       "  2014-01-06 15:00:00      9.4176  1516792706        9.81         1200.0   \n",
       "  ...                         ...         ...         ...            ...   \n",
       "  2017-09-29 15:00:00     41.4744  1516832834       15.71         3300.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832835       24.60          100.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832836        9.86          300.0   \n",
       "  2017-09-29 15:00:00     38.6432  1516832837       30.19         1600.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832838        3.83          500.0   \n",
       "  2017-09-29 15:00:00     42.5568  1516832839        4.29        12400.0   \n",
       "  2017-09-29 15:00:00     40.7744  1516832840       11.08         4600.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832841       24.97          200.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832842        6.31          600.0   \n",
       "  2017-09-29 15:00:00     45.1000  1516832843       22.55         2500.0   \n",
       "  2017-09-29 15:00:00     56.8384  1516832844        3.32        21400.0   \n",
       "  2017-09-29 15:00:00     32.2960  1516832845        7.34         5500.0   \n",
       "  2017-09-29 15:00:00     55.1120  1516832846        8.30         8300.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832847       13.93          100.0   \n",
       "  2017-09-29 15:00:00     56.3192  1516832848        7.91         8900.0   \n",
       "  2017-09-29 15:00:00     57.0360  1516832849        6.79        10500.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832850       17.87          100.0   \n",
       "  2017-09-29 15:00:00     35.4496  1516832851        3.82        11600.0   \n",
       "  2017-09-29 15:00:00     43.3280  1516832852       54.16         1000.0   \n",
       "  2017-09-29 15:00:00     15.6736  1516832853        6.32         3100.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832854        6.00          200.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832855       23.74          200.0   \n",
       "  2017-09-29 15:00:00     58.4584  1516832856        8.03         9100.0   \n",
       "  2017-09-29 15:00:00     57.6720  1516832857        4.05        17800.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832858       21.39          100.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832859        6.97          100.0   \n",
       "  2017-09-29 15:00:00     59.9872  1516832860        4.12        18200.0   \n",
       "  2017-09-29 15:00:00     15.2984  1516832861       14.71         1300.0   \n",
       "  2017-09-29 15:00:00      5.0000  1516832862        6.30          100.0   \n",
       "  2017-09-29 15:00:00     43.4592  1516832863       15.09         3600.0   \n",
       "  \n",
       "                      order_book_id    order_id position_effect  side symbol  \\\n",
       "  datetime                                                                     \n",
       "  2014-01-03 15:00:00   000063.XSHE  1516792676            None   BUY   中兴通讯   \n",
       "  2014-01-03 15:00:00   000961.XSHE  1516792677            None   BUY   中南建设   \n",
       "  2014-01-03 15:00:00   000983.XSHE  1516792678            None   BUY   西山煤电   \n",
       "  2014-01-03 15:00:00   600011.XSHG  1516792679            None   BUY   华能国际   \n",
       "  2014-01-03 15:00:00   600019.XSHG  1516792680            None   BUY   宝钢股份   \n",
       "  2014-01-03 15:00:00   600028.XSHG  1516792681            None   BUY   中国石化   \n",
       "  2014-01-03 15:00:00   600123.XSHG  1516792682            None   BUY   兰花科创   \n",
       "  2014-01-03 15:00:00   600157.XSHG  1516792683            None   BUY   永泰能源   \n",
       "  2014-01-03 15:00:00   600188.XSHG  1516792684            None   BUY   兖州煤业   \n",
       "  2014-01-03 15:00:00   600348.XSHG  1516792685            None   BUY   阳泉煤业   \n",
       "  2014-01-03 15:00:00   600362.XSHG  1516792686            None   BUY   江西铜业   \n",
       "  2014-01-03 15:00:00   600395.XSHG  1516792687            None   BUY   盘江股份   \n",
       "  2014-01-03 15:00:00   600403.XSHG  1516792688            None   BUY  *ST大有   \n",
       "  2014-01-03 15:00:00   600546.XSHG  1516792689            None   BUY   山煤国际   \n",
       "  2014-01-03 15:00:00   600971.XSHG  1516792690            None   BUY   恒源煤电   \n",
       "  2014-01-03 15:00:00   600997.XSHG  1516792691            None   BUY   开滦股份   \n",
       "  2014-01-03 15:00:00   601101.XSHG  1516792692            None   BUY   昊华能源   \n",
       "  2014-01-03 15:00:00   601186.XSHG  1516792693            None   BUY   中国铁建   \n",
       "  2014-01-03 15:00:00   601258.XSHG  1516792694            None   BUY   庞大集团   \n",
       "  2014-01-03 15:00:00   601299.XSHG  1516792695            None   BUY   中国北车   \n",
       "  2014-01-03 15:00:00   601328.XSHG  1516792696            None   BUY   交通银行   \n",
       "  2014-01-03 15:00:00   601699.XSHG  1516792697            None   BUY   潞安环能   \n",
       "  2014-01-03 15:00:00   601988.XSHG  1516792698            None   BUY   中国银行   \n",
       "  2014-01-06 15:00:00   000063.XSHE  1516792699            None   BUY   中兴通讯   \n",
       "  2014-01-06 15:00:00   000528.XSHE  1516792700            None   BUY     柳工   \n",
       "  2014-01-06 15:00:00   000961.XSHE  1516792701            None   BUY   中南建设   \n",
       "  2014-01-06 15:00:00   000983.XSHE  1516792702            None   BUY   西山煤电   \n",
       "  2014-01-06 15:00:00   600011.XSHG  1516792703            None   BUY   华能国际   \n",
       "  2014-01-06 15:00:00   600019.XSHG  1516792704            None   BUY   宝钢股份   \n",
       "  2014-01-06 15:00:00   600123.XSHG  1516792705            None   BUY   兰花科创   \n",
       "  ...                           ...         ...             ...   ...    ...   \n",
       "  2017-09-29 15:00:00   600060.XSHG  1516834879            None  SELL   海信电器   \n",
       "  2017-09-29 15:00:00   600066.XSHG  1516834880            None  SELL   宇通客车   \n",
       "  2017-09-29 15:00:00   600089.XSHG  1516834881            None  SELL   特变电工   \n",
       "  2017-09-29 15:00:00   600104.XSHG  1516834882            None  SELL   上汽集团   \n",
       "  2017-09-29 15:00:00   600170.XSHG  1516834883            None   BUY   上海建工   \n",
       "  2017-09-29 15:00:00   600208.XSHG  1516834884            None  SELL   新湖中宝   \n",
       "  2017-09-29 15:00:00   600376.XSHG  1516834885            None  SELL   首开股份   \n",
       "  2017-09-29 15:00:00   600585.XSHG  1516834886            None   BUY   海螺水泥   \n",
       "  2017-09-29 15:00:00   600688.XSHG  1516834887            None   BUY   上海石化   \n",
       "  2017-09-29 15:00:00   600741.XSHG  1516834888            None  SELL   华域汽车   \n",
       "  2017-09-29 15:00:00   600795.XSHG  1516834889            None   BUY   国电电力   \n",
       "  2017-09-29 15:00:00   600886.XSHG  1516834890            None  SELL   国投电力   \n",
       "  2017-09-29 15:00:00   600919.XSHG  1516834891            None   BUY   江苏银行   \n",
       "  2017-09-29 15:00:00   600926.XSHG  1516834892            None   BUY   杭州银行   \n",
       "  2017-09-29 15:00:00   601009.XSHG  1516834893            None   BUY   南京银行   \n",
       "  2017-09-29 15:00:00   601117.XSHG  1516834894            None   BUY   中国化学   \n",
       "  2017-09-29 15:00:00   601155.XSHG  1516834895            None   BUY   新城控股   \n",
       "  2017-09-29 15:00:00   601288.XSHG  1516834896            None  SELL   农业银行   \n",
       "  2017-09-29 15:00:00   601318.XSHG  1516834897            None  SELL   中国平安   \n",
       "  2017-09-29 15:00:00   601328.XSHG  1516834898            None   BUY   交通银行   \n",
       "  2017-09-29 15:00:00   601398.XSHG  1516834899            None   BUY   工商银行   \n",
       "  2017-09-29 15:00:00   601607.XSHG  1516834900            None  SELL   上海医药   \n",
       "  2017-09-29 15:00:00   601669.XSHG  1516834901            None   BUY   中国电建   \n",
       "  2017-09-29 15:00:00   601818.XSHG  1516834902            None   BUY   光大银行   \n",
       "  2017-09-29 15:00:00   601877.XSHG  1516834903            None   BUY   正泰电器   \n",
       "  2017-09-29 15:00:00   601939.XSHG  1516834904            None   BUY   建设银行   \n",
       "  2017-09-29 15:00:00   601988.XSHG  1516834905            None   BUY   中国银行   \n",
       "  2017-09-29 15:00:00   601997.XSHG  1516834906            None   BUY   贵阳银行   \n",
       "  2017-09-29 15:00:00   601998.XSHG  1516834907            None   BUY   中信银行   \n",
       "  2017-09-29 15:00:00   600690.XSHG  1516834908            None  SELL   青岛海尔   \n",
       "  \n",
       "                          tax     trading_datetime  transaction_cost  \n",
       "  datetime                                                            \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.1304  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            9.9648  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.3664  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.3584  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.2656  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.1616  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            9.8976  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.2336  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.4280  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.3208  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.3392  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            9.9936  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.3360  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.0672  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.3360  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.1760  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.0800  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.1248  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.1800  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.2600  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.3088  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00            9.7920  \n",
       "  2014-01-03 15:00:00   0.000  2014-01-03 15:00:00           10.2400  \n",
       "  2014-01-06 15:00:00   0.000  2014-01-06 15:00:00            8.7232  \n",
       "  2014-01-06 15:00:00   0.000  2014-01-06 15:00:00            8.5680  \n",
       "  2014-01-06 15:00:00   0.000  2014-01-06 15:00:00            9.5184  \n",
       "  2014-01-06 15:00:00   0.000  2014-01-06 15:00:00            8.8808  \n",
       "  2014-01-06 15:00:00   0.000  2014-01-06 15:00:00            9.1584  \n",
       "  2014-01-06 15:00:00   0.000  2014-01-06 15:00:00            5.0000  \n",
       "  2014-01-06 15:00:00   0.000  2014-01-06 15:00:00            9.4176  \n",
       "  ...                     ...                  ...               ...  \n",
       "  2017-09-29 15:00:00  51.843  2017-09-29 15:00:00           93.3174  \n",
       "  2017-09-29 15:00:00   2.460  2017-09-29 15:00:00            7.4600  \n",
       "  2017-09-29 15:00:00   2.958  2017-09-29 15:00:00            7.9580  \n",
       "  2017-09-29 15:00:00  48.304  2017-09-29 15:00:00           86.9472  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00  53.196  2017-09-29 15:00:00           95.7528  \n",
       "  2017-09-29 15:00:00  50.968  2017-09-29 15:00:00           91.7424  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00  56.375  2017-09-29 15:00:00          101.4750  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           56.8384  \n",
       "  2017-09-29 15:00:00  40.370  2017-09-29 15:00:00           72.6660  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           55.1120  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           56.3192  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           57.0360  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00  44.312  2017-09-29 15:00:00           79.7616  \n",
       "  2017-09-29 15:00:00  54.160  2017-09-29 15:00:00           97.4880  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           15.6736  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   4.748  2017-09-29 15:00:00            9.7480  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           58.4584  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           57.6720  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           59.9872  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00           15.2984  \n",
       "  2017-09-29 15:00:00   0.000  2017-09-29 15:00:00            5.0000  \n",
       "  2017-09-29 15:00:00  54.324  2017-09-29 15:00:00           97.7832  \n",
       "  \n",
       "  [40187 rows x 12 columns]}}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import rqalpha\n",
    "from rqalpha.api import *\n",
    "\n",
    "#读取文件位置\n",
    "def init(context):\n",
    "    context.codes = Intersection_weight\n",
    "    context.stocks = None\n",
    "    context.pos_weight = 0.9\n",
    "    scheduler.run_daily(find_pool)\n",
    "    \n",
    "\n",
    "def find_pool(context, bar_dict):\n",
    "    try:\n",
    "        codes = context.codes.loc[context.now].dropna()\n",
    "        context.stocks = codes\n",
    "    except:\n",
    "        context.stocks = None\n",
    "\n",
    "def handle_bar(context, bar_dict):\n",
    "    buy(context, bar_dict)\n",
    "\n",
    "\n",
    "def buy(context, bar_dict):\n",
    "    pool = context.stocks\n",
    "    if pool is not None:\n",
    "        for ins, percentage in pool.items():\n",
    "            order_target_percent(ins, percentage*context.pos_weight)\n",
    "        for ins in context.portfolio.positions:\n",
    "            if ins not in context.stocks:\n",
    "                order_target_percent(ins, 0)\n",
    "\n",
    "config = {\n",
    "  \"base\": {\n",
    "    \"start_date\": \"2014-01-03\",\n",
    "    \"end_date\": \"2018-01-31\",\n",
    "    \"accounts\": {'stock':10000000},\n",
    "    \"benchmark\": \"000300.XSHG\"\n",
    "  },\n",
    "  \"extra\": {\n",
    "    \"log_level\": \"error\",\n",
    "  },\n",
    "    \n",
    "  \"mod\": {\n",
    "    \"sys_analyser\": {\n",
    "      #\"enabled\": True,\n",
    "      \"plot\": True\n",
    "    },\n",
    "  }\n",
    "}\n",
    "\n",
    "rqalpha.run_func(init=init, handle_bar=handle_bar, config=config)"
   ]
  }
 ],
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